Detection and mitigation of denial of service attacks in distributed networking environments

ABSTRACT

Techniques for detecting and mitigating Denial of Service (DoS) attacks in distributed networking environment are disclosed. In certain embodiments, a DoS detection and mitigation system is disclosed that automatically monitors and analyzes network traffic data in a distributed networking environment using a set of pre-defined threshold criteria. The system includes capabilities for automatically invoking various mitigation techniques that take actions on malicious traffic based on the analysis and the pre-defined threshold criteria. The system includes capabilities for automatically detecting and mitigating “outbound” DoS attacks by analyzing network traffic data originating from an entity within the network to a public network (e.g., the Internet) outside the network as well as detect and mitigate “east-west” DoS attacks by analyzing network traffic data originating from a first entity located in a first data center of the network to a second entity located in a second data center of the network.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of, and claims the benefit ofand priority to, U.S. patent application Ser. No. 17/107,573, filed onNov. 30, 2020, the entire contents of which are incorporated herein byreference for all purposes.

BACKGROUND

Network security threats continue to be a huge problem with the risingpopularity of cloud-based services. It is a serious issue for bothconsumers and providers of cloud-based services. One common type ofnetwork security threat is a Denial of Service (DoS) attack which isinitiated by an attacker against a computer or a network of systems todeliberately restrict or prevent accessibility of resources toauthorized users. Individual networks may be affected by DoS attacks orthe infrastructure of a distributed computing environment hosted by thenetwork's internet service provider (ISP) or cloud service provider(CSP) can be targeted, resulting in a loss of service. A particularlyconcerning type of DoS attack is a volumetric DoS attack that occurswhen an attacker floods a network server with a high volume ofcommunication traffic. The volume of traffic can be so large that theattacked entity is no longer able to process legitimate traffic in atimely manner. The monitoring of systems and/or services to detectmalicious attacks especially in distributed computing environments isvery essential. DoS detection and mitigation approaches have beendeveloped that monitor network traffic and detect DoS attacks in suchenvironments. However, these approaches are limited in their ability toeffectively detect and reduce the impact of these types of attacks.

SUMMARY

This disclosure relates generally to detecting and mitigating DoSattacks in distributed networking environments. More specifically, butnot by way of limitation, this disclosure describes techniques formonitoring and analyzing network traffic data in a distributednetworking environment using a set of pre-defined threshold criteria.This disclosure additionally describes techniques for automaticallyinvoking various mitigation techniques that take actions on malicioustraffic based at least in part on the analysis and the pre-definedthreshold criteria. The actions allow only valid traffic to be forwardedback to the network and route the malicious traffic to a quarantinedenvironment, isolating it from production.

In one embodiment, a method for detecting and mitigating Denial ofService (DoS) attacks in a cloud services provider (CSP) network isdisclosed. The method includes for a first entity deployed in a firstregion of the CSP network, monitoring, by a computer system (e.g., a DoSdetection and monitoring system), a flow of network traffic dataoriginating from the first entity and destined to a second entity remotefrom the first entity. In certain examples, the CSP network isconfigured to provision a set of infrastructure resources for deploymentby at least the first entity in the first region of the CSP network. Themethod further includes determining, by the computer system, that theflow of network traffic data originating from the first entity exceeds athreshold value based on the monitoring. In certain examples, thethreshold value identifies at least one network traffic data valuerelated to the flow of network traffic data indicative of a Denial ofService (DoS) attack in the CSP network. The method then includesresponsive to the determining, identifying, by the computer system, anaction to be taken to mitigate the DoS attack in the CSP network andperforming, by the computer system, the action to mitigate the DoSattack in the CSP network.

In certain embodiments, the monitoring includes analyzing a plurality ofnetwork traffic data values related to the flow of network traffic datafrom a cluster of internal routing devices within the CSP network anddetermining that the network traffic data value related to the flow ofthe network traffic data exceeds a first threshold value based on theanalysis. In certain examples, the network traffic data value comprisesat least one of a packet generation frequency or a packet size relatedto packets in the flow of network traffic data.

In certain examples, the method further comprises transmitting a firstalert to a user of the CSP network based at least in part on determiningthat the network traffic data value related to the flow of networktraffic data exceeds the first threshold value. In certain examples, thefirst alert is transmitted as an email message to a user of the CSPnetwork.

In certain embodiments, monitoring the flow of network traffic dataoriginating from the first entity comprises analyzing the plurality ofnetwork traffic data values related to the flow of network traffic datafrom the cluster of internal routing devices within the CSP network andbased on the analysis, determining that the network traffic data valuerelated to the flow of network traffic data exceeds a second thresholdvalue. In certain examples, the second threshold value is greater thanthe first threshold value.

In certain examples, the method further comprises triggering an internalmitigation plan to mitigate the DoS attack based on determining that thenetwork traffic data value related to the flow of network traffic dataexceeds the second threshold value. In certain examples, the internalmitigation plan identifies a set of one or more actions to mitigate theDoS attack.

In certain embodiments, a first action in the set of one or more actionscauses an instruction to be transmitted by the computer system to acluster of internal routing devices within the CSP network to limit arate of the flow of network traffic data from the first entity to thesecond entity. A second action comprises transmitting, by the computersystem, an instruction to the cluster of internal routing devices to taga prefix of the Internet Protocol address of the first entity to blockthe flow of network traffic data transmitted from the first entity tothe second entity. A third action comprises an instruction transmittedby the computer system to the cluster of internal routing devices todivert the flow of network traffic data transmitted from the firstentity to a Remote triggered Blackhole (RTBH).

In certain embodiments, the second entity is deployed in a second regionof CSP network. The CSP network is configured to provision a set ofinfrastructure resources for deployment by the second entity in thesecond region. In certain embodiments, the second entity is an externalentity deployed in a network external to the CSP network. In certainembodiments, the DoS attack comprises at least one of a volumetric DoSattack or a volumetric Distributed DoS attack in the CSP network.

BRIEF DESCRIPTION OF THE DRAWINGS

Features, embodiments, and advantages of the present disclosure arebetter understood when the following Detailed Description is read withreference to the accompanying drawings.

FIG. 1 depicts a high level diagram of a distributed computingenvironment of a cloud services provider (CSP) network that includescapabilities for detecting and mitigating an “inbound” Denial of Service(DoS) attack within the CSP network, according to certain embodiments.

FIG. 2 is a high level diagram of a distributed environment showing aCSP network that includes capabilities for detecting and mitigating an“outbound” DoS attack within the CSP network, according to certainembodiments.

FIG. 3 is a high level diagram of a distributed environment showing aCSP network that includes capabilities for detecting and mitigating an“east-west” DoS attack within the CSP network, according to certainembodiments.

FIG. 4 is an example of a process for detecting and mitigating an“inbound” Denial of Service (DoS) attack within a CSP network, accordingto certain embodiments.

FIG. 5 is an example of a process for detecting and mitigating an“east-west” Denial of Service (DoS) attack within a CSP network,according to certain embodiments.

FIG. 6 is a block diagram illustrating one pattern for implementing acloud infrastructure as a service system, according to at least oneembodiment.

FIG. 7 is a block diagram illustrating another pattern for implementinga cloud infrastructure as a service system, according to at least oneembodiment.

FIG. 8 is a block diagram illustrating another pattern for implementinga cloud infrastructure as a service system, according to at least oneembodiment.

FIG. 9 is a block diagram illustrating another pattern for implementinga cloud infrastructure as a service system, according to at least oneembodiment.

FIG. 10 is a block diagram illustrating an example computer system,according to at least one embodiment.

DETAILED DESCRIPTION

In the following description, for the purposes of explanation, specificdetails are set forth in order to provide a thorough understanding ofcertain embodiments. However, it will be apparent that variousembodiments may be practiced without these specific details. The figuresand description are not intended to be restrictive. The word “exemplary”is used herein to mean “serving as an example, instance, orillustration.” Any embodiment or design described herein as “exemplary”is not necessarily to be construed as preferred or advantageous overother embodiments or designs.

In a cloud-based environment, users or customers can avail of servicesprovided by a cloud services provider (CSP) on demand (e.g., via asubscription model) using systems and infrastructure (cloudinfrastructure) provided by the CSP. For instance, the CSP can provideinfrastructure that can be used by customers to build their owncustomizable networks and deploy customer resources. The customer'sresources and networks are thus hosted in a distributed computingenvironment by infrastructure provided by the CSP. Detecting, preventingand/or minimizing DoS attacks in such distributed computing environmentscan be a challenging process. Typically the detection of attacks isperformed manually by a user (e.g., an administrator of the CSP network)who identifies the services and/or systems that have become unavailableand/or the entity that caused the attack within the distributedenvironment. For instance, the administrator may identify servicesand/or systems having technical problems while performing routinemaintenance of the CSP network as a symptom of a DoS attack. Symptoms ofa DoS attack may also detected when there is unusually slow networkperformance, unavailability of a system/service in the network and soon. In certain instances, the administrator may also manually analyzenetwork flow data statistics for different sampled flows of networktraffic data from devices (e.g., routers) within the computingenvironment to detect symptoms of DoS attacks. Oftentimes, this requiresseveral hours of troubleshooting by the administrator before an accuratediagnosis can be made and an appropriate action be taken.

The DoS Detection and Mitigation system described in the presentdisclosure provides several technical advancements over existing DoSdetection and mitigation capabilities available in distributed computingenvironments. The DoS Detection and Mitigation system described hereinautomatically detects and mitigates an impacting DoS attack before itcan cause link saturation and/or impact the infrastructure of adistributed computing environment. The DoS Detection and Mitigationsystem is very flexible and dynamic in nature. It includes capabilitiesfor analyzing network flow data statistics for different sampled flowsof network traffic data within the distributed computing environment andusing a set of pre-defined threshold criteria can automatically invokevarious mitigation techniques. The mitigation techniques take variousactions on malicious traffic by allowing only valid traffic to beforwarded back to the network and route the malicious traffic to aquarantined environment, isolating it from production.

In certain embodiments, the disclosed DoS Detection and Mitigationsystem includes capabilities for automatically detecting and mitigating“inbound” DoS attacks that occur as a result of network traffic datathat flows into the distributed computing environment of a CSP networkfrom an external network (e.g., the Internet). In certain embodiments,the system additionally includes capabilities for monitoring internaltraffic patterns within the distributed computing environment bymonitoring and analyzing network traffic data originating from entitieswithin the network. Unlike existing detection and mitigation approacheswhich primarily focus on securing external traffic entering theirnetworks, the disclosed system includes capabilities for monitoring andanalyzing internal traffic patterns that have infiltrated the networkfor detection of anomalies and insider threats. For example, thedisclosed system includes capabilities for detecting and mitigating“outbound” DoS attacks by analyzing network traffic data originatingfrom an entity within the network to a public network (e.g., theInternet) outside the network. In certain embodiments, the disclosedsystem includes capabilities for automatically detecting and mitigating“east-west” DoS attacks by analyzing network traffic data originatingfrom a first entity located in a first data center of the network to asecond entity located in a second data center of the network.

Referring now to the drawings, FIG. 1 depicts a high level diagram of adistributed computing environment 100 of a cloud services provider (CSP)network 102 that includes capabilities for detecting and mitigating aninbound Denial of Service (DoS) attack within the CSP network 102,according to certain embodiments. In the embodiment shown in FIG. 1 ,the devices, subsystems and services that make up the infrastructure ofthe CSP network 102 include an edge routing device 104, a cluster ofinternal routing devices 106A-106N, a DoS Detection and Mitigationsystem 108 and an internal mitigation service 110. In certainembodiments, the CSP network 102 comprises infrastructure that can beused by customers of the CSP network 102 to build their own customizablenetworks (e.g., 112, 114 and 116) and deploy customer resources. Thecustomer's resources and networks are thus hosted in a distributedenvironment by the infrastructure provided by the CSP network 102. Thecustomer can use these provisioned resources to build private networksand deploy resources on these networks. In certain examples, thecustomer networks 112, 114 and 116 that are hosted in the cloud by theCSP network 102 are referred to herein as virtual cloud networks (VCNs).Additional details of how customers can set up one or more virtual cloudnetworks (VCNs) using the CSP infrastructure resources allocated for thecustomer is discussed in FIG. 6 .

In certain embodiments, the resources of the CSP network 102 may bedistributed across one or more data centers that may be geographicallyspread across one or more regions. For instance, in the embodiment shownin FIG. 1 , the infrastructure provided by the CSP network 102 may bephysically hosted in a data center in a first region (e.g., NorthAmerica). The systems depicted in FIG. 1 may be implemented usingsoftware (e.g., code, instructions, program) executed by one or moreprocessing units (e.g., processors, cores) of a computing system,hardware, or combinations thereof. The software may be stored on anon-transitory storage medium (e.g., on a memory device). The CSPnetwork 102 depicted in FIG. 1 is merely an example and is not intendedto unduly limit the scope of claimed embodiments. One of ordinary skillin the art would recognize many possible variations, alternatives, andmodifications. For example, in some implementations, the CSP network 102can be implemented using more or fewer systems, customer networks, ordevices than those shown in FIG. 1 , may combine two or more systems, ormay have a different configuration or arrangement of systems.

In certain embodiments, the CSP network 102 provides improvedcapabilities for efficiently detecting and mitigating various types ofDoS attacks within the CSP network 102. Types of DoS attacks detected bythe CSP network 102 include, but are not limited to, Distributed DoS(DDoS) attacks where multiple systems simultaneously attack a singlesystem so that authorized clients are not able to get to the resourcesin the network, volumetric DoS attacks where resources in the network isconsumed by increasing the number of requests or packet sizes to exhaustserver processing and overload network resources, such as bandwidth inthe targeted network, volumetric DDoS attacks where the attackoriginates from a network of systems designed to send a high amount oftraffic, or packets, to a targeted network in an effort to overwhelm itsbandwidth capabilities and/or to saturate its resources and so on.

In the embodiment depicted in FIG. 1 , the DoS Detection and Mitigationsystem 108 includes capabilities to detect an “inbound” volumetric DoSattack within the CSP network 102. The detection is performed bymonitoring a flow of “incoming” network traffic data 122 as it entersthe edge of the CSP network 102 from an external/public network (e.g.,the Internet) 118. In an embodiment, the flow of incoming networktraffic data 122 is received by an edge routing device 104 within theCSP network 102. The edge routing device 104 may be a specialized routerthat acts as a gateway at the edge or boundary of the CSP network 102.The edge routing device 104 includes capabilities for sending andreceiving data directly to the CSP network 102 from the public network118 or vice versa. The edge routing device 104 thus acts as a connectionpoint between the CSP Network 102 and the public network 118 and ensuresconnectivity between the CSP network and the public network.

In certain examples, the edge routing device 104 may be configured withcapabilities to sample a subset of the flow of inbound network trafficdata 122 destined to a particular destination IP address (e.g., customernetwork 116) as it enters the CSP network 102. The rate at which theflow of network traffic data is sampled may be pre-configured by anadministrator of the CSP network 102 while setting up the infrastructureof the CSP network 102. By way of example, the edge routing device 104may be configured to sample only one network packet for every 1000network packets that it receives as part of the flow of network trafficdata. As used herein a “flow of network traffic data” may refer to aunidirectional stream of packets that arrive at the edge routing device104 having the same source and destination IP addresses. In a certainimplementation, the sampling may be performed by a network trafficanalyzer within the edge routing device 104. By way of example, thenetwork traffic analyzer may be implemented using the NetFlow® analyzerby Cisco Systems. The network traffic analyzer may be configured toaccumulate network flow data statistics (e.g., the point of origin,destination, bandwidth, and network paths) for different flows ofnetwork traffic data samples. The accumulated network flow datastatistics may subsequently be exported to a flow collection devicewithin the edge routing device 104 for further processing by the DoSDetection and Mitigation system 108.

In certain embodiments, the DoS Detection and Mitigation system 108 maybe configured to detect an “inbound” volumetric DoS attack on a customernetwork (e.g., 112, 114 or 116) based at least in part on analyzing thenetwork flow data statistics from the edge routing device 104. The DoSDetection and Mitigation system 108 may utilize any standard gatewayprotocol (e.g., Border Gateway Protocol (BGP)) to communicate with theedge routing device 104 for the exchange of routing and reachabilityinformation to perform its analysis. In certain examples, the analysismay involve, obtaining by the DoS Detection and Mitigation system 108,network traffic data statistics (values) related to a sampled flow ofnetwork traffic data such as the total duration of the sampled flow, thetotal number of packets in the sampled flow, the average packet size inthe sampled flow, the inter arrival time of the packets in the sampledflow, the packet generation frequency and so on.

Based at least in part on the analysis, the DoS Detection and Mitigationsystem 108 may be configured to automatically detect and mitigate animpacting “inbound” volumetric DoS attack on a customer network (e.g.,112, 114 or 116) within the CSP network 102. In certain examples, thedetection and mitigation is performed in two phases. In a first phase,based at least in part on the analysis of a sampled flow of networktraffic data (e.g., 122) from the edge routing device 104, the DoSDetection and Mitigation system 108 may trigger a “first level alert.”The “first level alert” (also referred to herein as a “low level alert”)may be sent as a pre-emptive measure to a user (e.g., an administrator)of the CSP network 102 of an impacting volumetric DoS attack that may bebuilding up that could affect a customer network or in-regioninfrastructure within the CSP network 102. In certain examples, the “lowlevel alert” may be triggered by the DoS Detection and Mitigation system108 when the packet generation frequency and/or packet size observedfrom the packets in a sampled flow of network traffic data meets orexceeds a first threshold value but is less than a second thresholdvalue. The threshold values (i.e., the first and second thresholdvalues) may be pre-configured values set by a user (e.g., anadministrator) of the CSP network 102 at the time of setting up theinfrastructure of the CSP network 102. The threshold values identifynetwork traffic data values (related to the flow of network trafficdata) indicative of an impacting volumetric DoS attack within the CSPnetwork. In certain examples, the first threshold value may be a valuethat is within a certain percentage (e.g., within plus or minus 25%) ofthe upper limit of the normal packet size in a flow of network trafficdata. By way of example, packets may be captured at a 1:1000 samplingrate and inspected for irregular packet sizes that may be larger orsmaller than the standard 1500 byte size. In this case, the firstthreshold value may be met when the packet size is larger than 1875bytes or smaller than 1125 bytes. This threshold value may be applicableto both TCP and UDP packets. Threshold values may also vary based onprotocol and the inspection being applied. As an example, a 10 Gbps linkcould trigger an initial threshold warning (“first level alert) at 2Gbps from any specific host generating network traffic or packetfrequencies of 500 Kbps. In certain examples, a “low level alert” mayalso be triggered by the DoS Detection and Mitigation system 108 basedon inspecting the payload of the packets with a known attack signature(or by creating a new signature) to block malicious network traffic. Incertain examples, the DoS Detection and Mitigation system 108 may beconfigured to transmit the “low level alert” as a message to theadministrator (or to a team of users) within the CSP network 102 via oneor more messaging applications.

In a second phase, the DoS Detection and Mitigation system 108 may beconfigured to trigger a “high level alert” based at least in part on theanalysis of the sampled flow of network traffic data from the edgerouting device 104. For instance, the “high level alert” may betriggered by the DoS Detection and Mitigation system 108 when the packetsize and/or the packet generation frequency in the sampled flow ofnetwork traffic reaches or exceeds a second threshold value. By way ofexample, the second threshold value may be set to a value that is withina certain percentage (e.g., within plus or minus 50%) of the upper limitof the normal packet size. Using the example above, a 10 Gbps link couldtrigger a “high level alert” at 4 Gbps from any specific host that isgenerating network traffic or packet frequencies of 1 Mbps. When the DoSDetection and Mitigation system 108 triggers a “high level alert,” itautomatically activates an internal mitigation plan to mitigate theattack before the attack can cause link saturation or impact theinfrastructure of the CSP network 102. In certain examples, the internalmitigation plan may identify a set of one or more actions for mitigatingthe attack. Each action may implement a specific mitigation technique onthe malicious traffic by allowing only valid traffic to be forwardedback to the network while routing malicious traffic to a quarantinedenvironment and isolating it from production.

For instance, if the DoS Detection and Mitigation system 108 determinesthat the attack is moderate, it may automatically invoke a first actionin the internal mitigation plan. A moderate attack may be determined,for example, if at least one network data traffic value (e.g., thepacket size and/or packet frequency) has exceeded the second thresholdvalue and the network bandwidth (i.e., measured by the maximum amount ofdata that can transferred from one point to another within the CSPnetwork 102 in a specific amount of time) increases to a certain valuewithin a specific amount of time. By way of example, the DoS Detectionand Mitigation system 108 may determine that the attack is moderate ifthe network bandwidth increases from 250 bits per second to 1000 kbitsper second within a few seconds and the packet size for the flow oftraffic has exceeded the second threshold value. In certain examples, animpact of an attack is defined based on traffic pattern variations.Network traffic data collected via the flow collection device mayprovide a baseline for normal traffic behavior over time. When trafficdiffers from the norm, it determines the severity of unusual activitybased on set thresholds of breach levels. These levels may also be setbased on acceptable traffic for each region.

In certain examples, the first action in the internal mitigation planmay, for instance, involve transmitting, by the DoS Detection andMitigation system 108, a command/instruction to the edge routing device104 to re-route the affected prefix (i.e., IP address identifying thecustomer network under attack) to an internal mitigation service 110.For instance, the DoS Detection and Mitigation system 108 may beconfigured to inject a /32 route (indicative of the first 32 bits of theIP address) to the edge routing device 104 which gets reflectedthroughout the routing tables and route-reflectors of the edge routingdevice. The edge routing device 104 may then be configured to channelthe specific IP address to the internal mitigation service 110. By wayof example, the internal mitigation service 110 may utilize a platform(e.g., based on the Arbor Networks Peakflow product) that is configuredwith the ability to divert the malicious traffic (i.e., the /32 IP beingattacked) while allowing only valid traffic to be forwarded back to theCSP network 102 thereby allowing the rest of the customers within theCSP network 102 to continue to operate without any service disruption.

If the DoS Detection and Mitigation system 108 determines that theimpending attack is relatively large (e.g., the attack has potentiallyinfrastructure impacting effects or may cause link saturation) or if theattack cannot effectively be mitigated by the internal mitigationsubsystem 110, the DoS Detection and Mitigation system 108 mayautomatically invoke a second action in the internal mitigation plan.The second action may involve, for instance, transmitting, by the DoSDetection and Mitigation system 108, an instruction to the edge routingdevice 104 to divert/re-route the malicious traffic to an upstream(external) mitigation service 120 that includes capabilities formonitoring the flow of network traffic directly through the edge routingdevice 104. The instructions may involve exchanging routing andreachability information with the edge routing device 104, performingconstant routing change lookups for the IP address under attack throughroute-view services provided by BGP, tagging the affected prefix with aBGP Community (e.g., a number value that the edge routing device useslike a tag) that will send a command to the edge routing device 104 toautomatically re-route the more specific IP address being attacked tothe external mitigation service 120 prior to it re-entering the CSPnetwork, performing route verification/leak checks and so on. In certainexamples, the external mitigation service 120 may be provided by athird-party flow-based monitoring service (e.g., Akamai's ProlexicFlow-Based Monitoring) that provides services for mitigating DoS attacksby directly monitoring the flow of network traffic through the edgerouting device 104 before it enters the CSP network 102.

If the attack is determined to be critical, requires immediate actionand/or cannot be handled either by the internal mitigation service 110or the external mitigation service 120, the DoS Detection and Mitigationsystem 108 may invoke a third action in the internal mitigation plan.This action may involve transmitting an instruction to the edge routingdevice to divert the traffic identifying the IP address under duress toa Remote triggered Blackhole (RTBH). RTBH is a filtering technique thatmay be used to effectively mitigate volumetric DoS attacks by filteringundesirable traffic even before it enters a protected network. Once anattack has been detected, RTBH filtering can be used to drop all attacktraffic at the edge of the CSP network 102, based on either destinationor source IP addresses.

Thus, by using a set of pre-defined threshold criteria, the disclosedDoS Detection and Mitigation system 108 may be configured toautomatically invoke various mitigation techniques to take actions onmalicious traffic by allowing only valid traffic to be forwarded back tothe network and routing the malicious traffic to a quarantinedenvironment, isolating it from production. In a traditional distributedenvironment without specific DoS detection techniques in place, DoSdetection and mitigation is conventionally performed manually. Aspreviously described, for instance, the detection is usually performedby a user (e.g., an administrator) within the CSP network 102 who has tomanually identify the services and/or systems that have becomeunavailable and/or identify the entity (i.e., origin) that caused theattack. This may take several hours of troubleshooting by theadministrator before a correct diagnosis can be made. For instance, theadministrator may manually analyze network flow data statistics fordifferent sampled flows of network traffic data from the edge routingdevice 104 before making an accurate diagnosis. Upon detecting anattack, the administrator then issues a command to a third party service(e.g., the internal mitigation service 110) to divert the malicioustraffic to a quarantined environment and isolating it from production.

The DoS Detection and Mitigation system 108 described in the presentdisclosure provides several technical advancements over existing DoSdetection and mitigation capabilities available in distributed computingenvironments. The DoS Detection and Mitigation system described hereinautomatically detects and mitigates an impacting DoS attack before itcan cause link saturation and/or impact the infrastructure of adistributed computing environment. The disclosed technique additionallyeliminates the need for a user (e.g., an administrator) of the CSPnetwork 102 to manually analyze network flow data statistics fordifferent sampled flows of network traffic data and/or to communicatewith a third party service to make decisions about the appropriateaction to take when an attack is detected.

In certain embodiments such as the embodiment depicted in FIG. 1 , theDoS Detection and Mitigation system 108 included capabilities fordetecting and mitigating an “inbound” volumetric DoS attack within theCSP network 102 by analyzing an “incoming” flow of network traffic datareceived from an external network (e.g., the Internet) 118 and directedto a particular destination address (e.g., a customer network, 112, 114or 116) within the CSP network 102. However, in certain situations, thecomputing instance that is generating the malicious network traffic mayoriginate from within the CSP network 102 itself. For example, themalicious traffic may originate from an entity such as a customernetwork (e.g., 112, 114 or 116) within the CSP network 102. Such anentity may overwhelm the CSP network 102 by generating a flood of“outgoing” network traffic data making the CSP network 102 and/or someof its services unavailable. In certain embodiments, and as will bedescribed in detail in FIG. 2 , the DoS Detection and Mitigation system108 additionally includes capabilities for detecting and mitigating“outbound” volumetric DoS attacks by analyzing an “outgoing” flow ofnetwork traffic originating from a customer network. The DoS Detectionand Mitigation system 108 automatically invokes various mitigationtechniques to take action on the malicious traffic based at least inpart on the analysis.

FIG. 2 is a high level diagram of a distributed environment 200 showinga CSP network 102 that includes capabilities for detecting andmitigating an “outbound” DoS attack within the CSP network 102,according to certain embodiments. In the embodiment depicted in FIG. 2 ,an “outgoing” flow of network traffic data 202 originates from acustomer network 116. The “outgoing” flow 202 natively flows from thecustomer network 116 to a cluster of internal routing devices 106A-106Nwithin the CSP network 102 that are configured to intercept and samplethe flow 202 prior to transmitting the network traffic data to anendpoint (e.g., the Internet 118) outside the CSP network 102. Since the“outgoing” flow 202 from the customer network 116 natively flows towardsthe cluster of internal routing devices 106A-106N, the internal routingdevices may be configured with capabilities to monitor a subset (or asample) of the outgoing flow 202 as it leaves the CSP network 116. In acertain implementation, the cluster of internal routing devices106A-106N may include a network traffic analyzer (similar to the networktraffic analyzer described in FIG. 1 ) for sampling and accumulatingnetwork flow data statistics for different outbound flows of networktraffic data. The accumulated network flow data statistics maysubsequently be exported to a flow collection device within the internalrouting devices 106A-106N for further processing by the DoS Detectionand Mitigation system 108.

In certain embodiments, the DoS Detection and Mitigation system 108 maybe configured to detect and mitigate an “outbound” volumetric DoS attackoriginating from a customer network (e.g., 116) by analyzing the networkflow data statistics for the sampled outgoing flow 202 from the internalrouting devices 106A-106N. The DoS Detection and Mitigation system 108may utilize any standard gateway protocol (e.g., BGP) to communicatewith the internal routing devices 106A-106N for the exchange of routingand reachability information to perform its analysis. As previouslydescribed in the description of FIG. 1 , the analysis may involve,obtaining by the DoS Detection and Mitigation system 108, network flowdata statistics related to the sampled flow 202 such as the totalduration of the sampled flow, the total number of packets in the sampledflow, the average packet size in the sampled flow, the inter arrivaltime of the packets in the sampled flow, the packet generation frequencyand so on.

Based at least in part on the analysis, the DoS Detection and Mitigationsystem 108 may be configured to automatically detect and mitigate an“outbound” volumetric DoS attack originating from the customer network116. In certain examples, the detection and mitigation may be performedin a manner similar to the technique described in FIG. 1 for inboundattacks. For instance, in a first phase, based at least in part on theanalysis of a sampled outgoing flow of network traffic data from acustomer network, the DoS Detection and Mitigation system 108 maytrigger a “low level alert.” The “low level alert” may be indicative ofa pre-emptive measure of any potential “outbound” volumetric DoS attackthat may be building up that could affect the in-region infrastructureand/or services within the CSP network 102. For instance, a “low levelalert” may be triggered by the DoS Detection and Mitigation system 108when the packet generation frequency and/or packet size observed from asampled outgoing flow of network traffic data from a customer network(e.g., 112, 114 or 116) meets or exceeds a first threshold value but isless than a second threshold value. The threshold values may bepre-configured by an administrator of the CSP network 102 while settingup the infrastructure of the CSP network 102. The “low level alert” maybe transmitted as a message to the administrator of the CSP network 102.

In a second phase, the DoS Detection and Mitigation system 108 may beconfigured to trigger a “high level alert” based at least in part on theanalysis of the sampled outgoing flow of network traffic data from thecluster of internal routing devices 106A-106N. For instance, the “highlevel alert” may be triggered by the DoS Detection and Mitigation system108 when the packet size and/or the packet generation frequency in thesampled flow of network traffic reaches or exceeds a second thresholdvalue. When the DoS Detection and Mitigation system 108 triggers a “highlevel alert,” it automatically activates an internal mitigation plan tomitigate the “outbound” volumetric DoS attack before the attack cancause link saturation or impact the infrastructure of the CSP network102. The internal mitigation plan may identify a set of one or moreactions for mitigating the attack. For instance, in this embodiment, afirst action to mitigate an “outbound” volumetric DoS attack mayinvolve, transmitting, by the DoS Detection and Mitigation system 108 acommand/instruction to the internal routing devices 106A-106N to limitthe rate of the outgoing flow of network traffic data from the customernetwork to be within a pre-set rate limit threshold. By way of example,for a volumetric DoS attack identified as a DoS amplification attack,the pre-set rate limit threshold may be in the range of 200 Mbps-4 Gbps,for a volumetric DoS attack identified as a DNS (Domain Name Server)amplification attack, the pre-set rate limit threshold may be in therange of 60 Kpps-600 Kpps, for a volumetric DoS attack identified as anNTP (Network Time Protocol) amplification attack, the pre-set rate limitthreshold may be in the range of 100 Kpps-1 Mpps, for a volumetric DoSattack identified a TCP SYN/ACK amplification attack, the pre-set ratelimit threshold may be in the range of 100 Kpps-2 Mpps, for a volumetricDoS attack identified a UDP attack, the pre-set rate limit threshold maybe in the range of 200 Mpps-4Gpps, for an ICMP (Internet Control MessageProtocol) fragmentation attack, the pre-set rate limit threshold may bein the range of 60 Kpps-250 Kpps, for an IP fragment attack, the pre-setrate limit threshold may be in the range of 60 Kpps-250 Kpps and so on.

A second action may involve, transmitting, by the DoS Detection andMitigation system 108, a command to the internal routing devices106A-106N to tag the affected prefix with a BGP community to take actiononly on the prefix generating the attack (for e.g., by blocking the flowof network traffic data transmitted from the first entity) whileallowing the rest of the customers in that production environment tocontinue to operate without any service disruption. If the attack isdetermined to be critical, requires immediate action and/or cannot behandled by the internal routing devices, the DoS Detection andMitigation system 108 may invoke a third action in the internalmitigation plan. This action may involve transmitting an instruction tothe cluster of internal routing devices to completely block the trafficby identifying the IP address under duress and diverting the traffic toa Remote triggered Blackhole (RTBH).

The systems depicted in FIG. 2 may be implemented using software (e.g.,code, instructions, program) executed by one or more processing units(e.g., processors, cores) of a computing system, hardware, orcombinations thereof. The software may be stored on a non-transitorystorage medium (e.g., on a memory device). The CSP network 102 depictedin FIG. 2 is merely an example and is not intended to unduly limit thescope of claimed embodiments. One of ordinary skill in the art wouldrecognize many possible variations, alternatives, and modifications. Forexample, in some implementations, the CSP network 102 can be implementedusing more or fewer systems, devices, and/or customer networks thanthose shown in FIG. 2 , may combine two or more systems, or may have adifferent configuration or arrangement of systems.

In the embodiments depicted in FIG. 1 and FIG. 2 , the infrastructureprovided by the CSP network 102 was physically hosted in a single datacenter in a region (e.g., North America). In alternate embodiments, theresources of the CSP network 102 may be spread across one or more datacenters that may be geographically spread across one or more regions.For instance, the infrastructure provided by the CSP network 102 may bephysically hosted in two data centers in two different regions, NorthAmerica and Europe. In certain embodiments, the DoS Detection andMitigation system 108 includes capabilities for detecting and mitigatingvolumetric DoS attacks within the CSP network that occur as a result ofnetwork traffic data that flows in an “east-west” direction within theCSP network. As used herein, “east-west” network traffic data refers totraffic that flows between one or more entities within a data center ofthe CSP network or between entities in two different data centers of theCSP network. For instance, “east-west” network traffic data may refer totraffic that flows from a first entity (e.g., a first customer network)in a first data center of the CSP network located in a first region to asecond entity (e.g., a second customer network) in a second data centerof the CSP network located in a second region.

Thus, in addition to detecting and mitigating DoS attacks that occur asa result of network traffic data that flows in the “north-south”direction or in the “south-north” direction within the CSP networkdescribed in FIGS. 1 and 2 which typically indicates the flow of networktraffic data from a public network to a data center of the CSP networkand vice versa, the DoS Detection and Mitigation system 108 includescapabilities for detecting and mitigating DoS attacks that occur as aresult of “east-west” network traffic data between entities located indifferent data centers of the CSP network.

The DoS Detection and Mitigation system 108 described in the presentdisclosure provides several technical advancements over conventionalnetworking environments that at best include capabilities for detectingand mitigating “inbound” DoS attacks that occur as a result of networktraffic data that flows in the “north-south” direction. By includingcapabilities to detect and mitigate “outbound” DoS attacks that occur asa result of network traffic data that flows in the “south-north”direction as well “east-west” DoS attacks that occur as a result ofnetwork traffic data that flows in the “east-west” direction, internaltraffic patterns within the distributed computing environment that haveinfiltrated the network can be monitored for detection of anomalies andinsider threats. Visibility into east-west traffic is critical fororganizations to determine the best security practices for theirnetworks and data centers. While many organizations tend to focus onsecuring external traffic that enters their networks, it is increasinglyimportant for organizations to monitor internal traffic patterns formalware that has infiltrated the network and insider threats. Theembodiment shown in FIG. 3 describes the capabilities of the DoSDetection and Mitigation system 108 for detecting and mitigating DoSattacks that occur as a result of “east-west” network traffic databetween entities located in different data centers of the CSP network.

FIG. 3 is a high level diagram of a distributed environment 300 showinga CSP network 102 that includes capabilities for detecting andmitigating an “east-west” DoS attack within the CSP network, accordingto certain embodiments. In the embodiment depicted in FIG. 3 , a firstentity (e.g., customer network 116) deployed in a first data center in afirst region 302 of the CSP network transmits a flow of network trafficdata 312 to a second entity (e.g., customer network 310) deployed in asecond data center in a second region 304 of the CSP network. The“east-west” flow of network traffic data 312 natively flows from thecustomer network 116 to a cluster of internal routing devices 106A-106Nlocated in the CSP network in the first region 302 that are configuredto intercept and sample the flow 312 prior to transmitting the networktraffic data to an endpoint (e.g., a cluster of internal routing devices308A-308N) located in a second region 304 of the CSP network. In certainexamples, the cluster of internal routing devices 106A-106N in the firstregion 302 may be configured with capabilities to monitor a subset (or asample) of the flow 312 as it leaves the first region 302 of the CSPnetwork. In a certain implementation, the cluster of internal routingdevices 106A-106N may include a network traffic analyzer (similar to thenetwork traffic analyzer described in FIGS. 1 and 2 ) that includescapabilities for sampling and accumulating network flow data statisticsfor “east-west” flows of network traffic data. The accumulated networkflow data statistics may subsequently be exported to a flow collectiondevice within the internal routing devices 106A-106N for furtherprocessing by the DoS Detection and Mitigation system 108.

In certain embodiments, the DoS Detection and Mitigation system 108 maybe configured to detect an “east-west” volumetric DoS attack originatingfrom a customer network (e.g., 116) located in a first region 302 of theCSP network by analyzing network flow data statistics for the sampledflow 312 from the internal routing devices 106A-106N. The DoS Detectionand Mitigation system 108 may utilize any standard gateway protocol(e.g., BGP) to communicate with the internal routing devices 106A-106Nfor the exchange of routing and reachability information to perform itsanalysis. As previously described in the description of FIGS. 1 and 2 ,the analysis may involve, obtaining by the DoS Detection and Mitigationsystem 108, network flow data statistics related to the sampled flow 312such as the total duration of the sampled flow, the total number ofpackets in the sampled flow, the average packet size in the sampledflow, the inter arrival time of the packets in the sampled flow, thepacket generation frequency and so on.

Based at least in part on the analysis, the DoS Detection and Mitigationsystem 108 may be configured to automatically detect and mitigate an“east west” volumetric DoS attack originating from the customer network116 in the first region 302 to a different customer network 310 in asecond region 304 of the CSP network. In certain examples, the detectionand mitigation may be performed in a manner similar to the techniquedescribed for detecting and mitigating an “outbound volumetric DoS”attack described in FIG. 2 . For instance, in a first phase, based atleast in part on the analysis of a sampled “east-west” flow of networktraffic data from the first customer network (e.g., 116) to the secondcustomer network (e.g., 310), the DoS Detection and Mitigation system108 may trigger a “low level alert.” The “low level alert” may beindicative of a pre-emptive measure of any potential “outbound” DoSattack that may be building up that could affect the in-regioninfrastructure within the CSP network in the first region 302. Forinstance, a “low level alert” may be triggered by the DoS Detection andMitigation system 108 when the packet generation frequency and/or packetsize observed from a sampled flow of network traffic data from acustomer network (e.g., 112, 114 or 116) meets or exceeds a firstthreshold value but is less than a second threshold value. The thresholdvalues may be pre-configured by an administrator of the CSP network 102while setting up the infrastructure of the CSP network 102. The “lowlevel alert” may be transmitted as a message to the administrator of theCSP network 102.

In a second phase, the DoS Detection and Mitigation system 108 may beconfigured to trigger a “high level alert” based at least in part on theanalysis of the sampled flow of network traffic data from the cluster ofinternal routing devices 106A-106N. For instance, the “high level alert”may be triggered by the DoS Detection and Mitigation system 108 when thepacket size and/or the packet generation frequency (packets per secondor bytes per second) reaches or exceeds a second threshold value. Thesecond threshold value may be pre-configured by an administrator of theCSP network 102 while setting up the infrastructure of the CSP network102. When the DoS Detection and Mitigation system 108 triggers a “highlevel alert,” it automatically activates an internal mitigation plan tomitigate the “east-west” DoS attack before the attack can cause linksaturation or impact the infrastructure of the CSP network 102. Theinternal mitigation plan may identify a set of one or more actions formitigating the attack. For instance, in this embodiment, a first actionto mitigate an “east-west” volumetric DoS attack may involve,transmitting, by the DoS Detection and Mitigation system 108 acommand/instruction to the internal routing devices 106A-106N to limitthe rate of flow of network traffic data from the first customer network116 to be within a pre-set rate limit threshold. A second action mayinvolve, transmitting, by the DoS Detection and Mitigation system 108, acommand to the internal routing devices 106A-106N to tag the affectedprefix with a BGP community to take action only on the prefix generatingthe attack (for e.g., by blocking the flow of network traffic datatransmitted from the first entity) while allowing the rest of thecustomers in that production environment to continue to operate withoutany service disruption.

If the attack is determined to be critical, requires immediate actionand/or cannot be handled either by the internal routing devices, the DoSDetection and Mitigation system 108 may invoke a third action in theinternal mitigation plan. This action may involve transmitting aninstruction to the cluster of internal routing devices to completelyblock/divert the traffic by identifying the IP address under duress anddiverting the traffic to a Remote triggered Blackhole (RTBH).

The systems depicted in FIG. 3 may be implemented using software (e.g.,code, instructions, program) executed by one or more processing units(e.g., processors, cores) of a computing system, hardware, orcombinations thereof. The software may be stored on a non-transitorystorage medium (e.g., on a memory device). The CSP network located inthe first region 302 and the second region 304 depicted in FIG. 3 aremerely examples and are not intended to unduly limit the scope ofclaimed embodiments. One of ordinary skill in the art would recognizemany possible variations, alternatives, and modifications. For example,in some implementations, the CSP network can be implemented using moreor fewer subsystems, more or fewer customer networks and in more orfewer regions than those shown in FIG. 3 , may combine two or moresystems, or may have a different configuration or arrangement ofsystems.

FIG. 4 is an example of a process for detecting and mitigating an“inbound” Denial of Service (DoS) attack within a CSP network, accordingto certain embodiments. The processing depicted in FIG. 4 may beimplemented in software only (e.g., code, instructions, program)executed by one or more processing units (e.g., processors, cores) ofthe respective systems, hardware only, or combinations thereof. Thesoftware may be stored on a non-transitory storage medium (e.g., on amemory device). The process 400 presented in FIG. 4 and described belowis intended to be illustrative and non-limiting. Although FIG. 4 depictsthe various processing steps occurring in a particular sequence ororder, this is not intended to be limiting. In certain alternativeembodiments, the steps may be performed in some different order or somesteps may also be performed in parallel. In certain embodiments, such asin the embodiment depicted in FIG. 1 , the processing depicted in FIG. 4may be performed by the DoS Detection and Mitigation system 108.

The processing depicted in FIG. 4 is initiated at block 402 when the DoSDetection and Mitigation system 108 analyzes network traffic data valuesrelated to a flow of network traffic data from an edge routing device(e.g., 104) within the CSP network (e.g., 102). As previously described,the analysis may involve, obtaining by the DoS Detection and Mitigationsystem 108, network traffic data statistics (values) related to asampled flow of network traffic data such as the total duration of thesampled flow, the total number of packets in the sampled flow, theaverage packet size in the sampled flow, the inter arrival time of thepackets in the sampled flow, the packet generation frequency and so on.

At block 404, the DoS Detection and Mitigation system 108 performs acheck to determine that at least one network traffic data value is equalto or greater than a first threshold value but less than a secondthreshold value. The threshold values (i.e., the first and secondthreshold value) identify network traffic data values (e.g., packetsize, packet generation frequency and so on related to the flow ofnetwork traffic data) indicative of an impacting volumetric DoS attackwithin the CSP network. The threshold values may be pre-configuredvalues set by a user (e.g., an administrator) of the CSP network 102 atthe time of setting up the infrastructure of the CSP network 102.

If the network traffic data value is equal to or greater than a firstthreshold value but less than a second threshold value, at block 406,the DoS Detection and Mitigation system 108 transmits an alert (e.g., alow level alert) to a user (e.g., an administrator) of the CSP network.As previously described, the low level alert may be sent as apre-emptive measure to an administrator of the CSP network 102 of animpacting volumetric DoS attack that may be building up that couldaffect a customer network or in-region infrastructure within the CSPnetwork 102. For example, the “low level alert” may be transmitted as amessage to the administrator (or to a team of users) within the CSPnetwork 102 via one or more messaging applications.

If the network traffic data value is greater than a second thresholdvalue, at block 408, the DoS Detection and Mitigation system 108triggers an internal mitigation plan to mitigate the DoS attack. Theinternal mitigation plan may identify a set of one or more actions formitigating the attack. For example, a first option at block 410 mayinvolve, transmitting, by the DoS Detection and Mitigation system 108, acommand to the edge routing device 104 to re-route the affected prefix(i.e., IP address identifying the customer network under attack) to aninternal mitigation service (e.g., 110). A second option at block 412may involve, transmitting, by the DoS Detection and Mitigation system108, an instruction/command to the edge routing device 104 todivert/re-route the malicious traffic to an upstream (external)mitigation service (e.g., 120). A third option at block 414 may involvediverting the traffic identifying the IP address under duress to aRemote triggered Blackhole (RTBH).

FIG. 5 is an example of a process for detecting and mitigating an“east-west” Denial of Service (DoS) attack within a CSP network,according to certain embodiments. The processing depicted in FIG. 5 maybe implemented in software only (e.g., code, instructions, program)executed by one or more processing units (e.g., processors, cores) ofthe respective systems, hardware only, or combinations thereof. Thesoftware may be stored on a non-transitory storage medium (e.g., on amemory device). The process 500 presented in FIG. 5 and described belowis intended to be illustrative and non-limiting. Although FIG. 5 depictsthe various processing steps occurring in a particular sequence ororder, this is not intended to be limiting. In certain alternativeembodiments, the steps may be performed in some different order or somesteps may also be performed in parallel. In certain embodiments, such asin the embodiment depicted in FIG. 3 , the processing depicted in FIG. 5may be performed by the DoS Detection and Mitigation system 108.

The processing depicted in FIG. 5 is initiated at block 502 when the DoSDetection and Mitigation system 108 analyzes network traffic data valuesrelated to a flow of network traffic data from a cluster of internalrouting devices (e.g., 106A-106N). For example, the flow of networktraffic data may be transmitted by a first entity (e.g., a customernetwork 116) deployed in a first region 302 of the CSP network to asecond entity (e.g. a customer network 310) deployed in a second region304 of the CSP network. As previously described, the analysis mayinvolve, obtaining by the DoS Detection and Mitigation system 108,network traffic data statistics (values) related to a sampled flow ofnetwork traffic data from the first entity such as the total duration ofthe sampled flow, the total number of packets in the sampled flow, theaverage packet size in the sampled flow, the inter arrival time of thepackets in the sampled flow, the packet generation frequency and so on.

At block 504, the DoS Detection and Mitigation system 108 performs acheck to determine that at least one network traffic data value is equalto or greater than a first threshold value but less than a secondthreshold value. The threshold values (i.e., the first and secondthreshold value) identify network traffic data values (e.g., packetsize, packet generation frequency and so on related to the flow ofnetwork traffic data) indicative of an impacting volumetric DoS attackwithin the CSP network. The threshold values may be pre-configuredvalues set by a user (e.g., an administrator) of the CSP network 102 atthe time of setting up the infrastructure of the CSP network 102.

If the network traffic data value is equal to or greater than a firstthreshold value but less than a second threshold value, at block 506,the DoS Detection and Mitigation system 108 transmits an alert (e.g., alow level alert) to a user (e.g., an administrator) of the CSP network.As previously described, the low level alert may be sent as apre-emptive measure to an administrator of the CSP network 102 of animpacting volumetric DoS attack that may be building up that couldaffect a customer network or in-region infrastructure within the CSPnetwork 102. For example, the “low level alert” may be transmitted as amessage to the administrator (or to a team of users) within the CSPnetwork 102 via one or more messaging applications.

If the network traffic data value is greater than a second thresholdvalue, at block 508, the DoS Detection and Mitigation system 108triggers an internal mitigation plan to mitigate the DoS attack. Theinternal mitigation plan, may identify a set of one or more actions formitigating the attack. For example, in this embodiment, a first optionat block 510 may involve, transmitting, by the DoS Detection andMitigation system 108, a command to the cluster of internal routingdevices to limit the rate of traffic flow from the first entity to thesecond entity. A second option at block 512 may involve, transmitting,by the DoS Detection and Mitigation system 108, an instruction/commandto the cluster of internal routing devices to tag the affected prefixwith a BGP community to take action only on the prefix generating theattack (for e.g., by blocking the flow of network traffic datatransmitted from the first entity) while allowing the rest of thecustomers in that production environment to continue to operate withoutany service disruption. A third option at block 514 may involvediverting the traffic identifying the IP address under duress to aRemote triggered Blackhole (RTBH).

Example Architectures

As noted above, infrastructure as a service (IaaS) is one particulartype of cloud computing. IaaS can be configured to provide virtualizedcomputing resources over a public network (e.g., the Internet). In anIaaS model, a cloud computing provider can host the infrastructurecomponents (e.g., servers, storage devices, network nodes (e.g.,hardware), deployment software, platform virtualization (e.g., ahypervisor layer), or the like). In some cases, an IaaS provider mayalso supply a variety of services to accompany those infrastructurecomponents (e.g., billing, monitoring, logging, security, load balancingand clustering, etc.). Thus, as these services may be policy-driven,IaaS users may be able to implement policies to drive load balancing tomaintain application availability and performance.

In some instances, IaaS customers may access resources and servicesthrough a wide area network (WAN), such as the Internet, and can use thecloud provider's services to install the remaining elements of anapplication stack. For example, the user can log in to the IaaS platformto create virtual machines (VMs), install operating systems (OSs) oneach VM, deploy middleware such as databases, create storage buckets forworkloads and backups, and even install enterprise software into thatVM. Customers can then use the provider's services to perform variousfunctions, including balancing network traffic, troubleshootingapplication issues, monitoring performance, managing disaster recovery,etc.

In most cases, a cloud computing model will require the participation ofa cloud provider. The cloud provider may, but need not be, a third-partyservice that specializes in providing (e.g., offering, renting, selling)IaaS. An entity might also opt to deploy a private cloud, becoming itsown provider of infrastructure services.

In some examples, IaaS deployment is the process of putting a newapplication, or a new version of an application, onto a preparedapplication server or the like. It may also include the process ofpreparing the server (e.g., installing libraries, daemons, etc.). Thisis often managed by the cloud provider, below the hypervisor layer(e.g., the servers, storage, network hardware, and virtualization).Thus, the customer may be responsible for handling (OS), middleware,and/or application deployment (e.g., on self-service virtual machines(e.g., that can be spun up on demand) or the like.

In some examples, IaaS provisioning may refer to acquiring computers orvirtual hosts for use, and even installing needed libraries or serviceson them. In most cases, deployment does not include provisioning, andthe provisioning may need to be performed first.

In some cases, there are two different problems for IaaS provisioning.First, there is the initial challenge of provisioning the initial set ofinfrastructure before anything is running. Second, there is thechallenge of evolving the existing infrastructure (e.g., adding newservices, changing services, removing services, etc.) once everythinghas been provisioned. In some cases, these two challenges may beaddressed by enabling the configuration of the infrastructure to bedefined declaratively. In other words, the infrastructure (e.g., whatcomponents are needed and how they interact) can be defined by one ormore configuration files. Thus, the overall topology of theinfrastructure (e.g., what resources depend on which, and how they eachwork together) can be described declaratively. In some instances, oncethe topology is defined, a workflow can be generated that creates and/ormanages the different components described in the configuration files.

In some examples, an infrastructure may have many interconnectedelements. For example, there may be one or more virtual private clouds(VPCs) (e.g., a potentially on-demand pool of configurable and/or sharedcomputing resources), also known as a core network. In some examples,there may also be one or more security group rules provisioned to definehow the security of the network will be set up and one or more virtualmachines (VMs). Other infrastructure elements may also be provisioned,such as a load balancer, a database, or the like. As more and moreinfrastructure elements are desired and/or added, the infrastructure mayincrementally evolve.

In some instances, continuous deployment techniques may be employed toenable deployment of infrastructure code across various virtualcomputing environments. Additionally, the described techniques canenable infrastructure management within these environments. In someexamples, service teams can write code that is desired to be deployed toone or more, but often many, different production environments (e.g.,across various different geographic locations, sometimes spanning theentire world). However, in some examples, the infrastructure on whichthe code will be deployed must first be set up. In some instances, theprovisioning can be done manually, a provisioning tool may be utilizedto provision the resources, and/or deployment tools may be utilized todeploy the code once the infrastructure is provisioned.

FIG. 6 is a block diagram 600 illustrating an example pattern of an IaaSarchitecture, according to at least one embodiment. Service operators602 can be communicatively coupled to a secure host tenancy 604 that caninclude a virtual cloud network (VCN) 606 and a secure host subnet 608.In some examples, the service operators 602 may be using one or moreclient computing devices, which may be portable handheld devices (e.g.,an iPhone®, cellular telephone, an iPad®, computing tablet, a personaldigital assistant (PDA)) or wearable devices (e.g., a Google Glass® headmounted display), running software such as Microsoft Windows Mobile®,and/or a variety of mobile operating systems such as iOS, Windows Phone,Android, BlackBerry 8, Palm OS, and the like, and being Internet,e-mail, short message service (SMS), Blackberry®, or other communicationprotocol enabled. Alternatively, the client computing devices can begeneral purpose personal computers including, by way of example,personal computers and/or laptop computers running various versions ofMicrosoft Windows®, Apple Macintosh®, and/or Linux operating systems.The client computing devices can be workstation computers running any ofa variety of commercially-available UNIX® or UNIX-like operatingsystems, including without limitation the variety of GNU/Linux operatingsystems, such as for example, Google Chrome OS. Alternatively, or inaddition, client computing devices may be any other electronic device,such as a thin-client computer, an Internet-enabled gaming system (e.g.,a Microsoft Xbox gaming console with or without a Kinect® gesture inputdevice), and/or a personal messaging device, capable of communicatingover a network that can access the VCN 606 and/or the Internet.

The VCN 606 can include a local peering gateway (LPG) 610 that can becommunicatively coupled to a secure shell (SSH) VCN 612 via an LPG 610contained in the SSH VCN 612. The SSH VCN 612 can include an SSH subnet614, and the SSH VCN 612 can be communicatively coupled to a controlplane VCN 616 via the LPG 610 contained in the control plane VCN 616.Also, the SSH VCN 612 can be communicatively coupled to a data plane VCN618 via an LPG 610. The control plane VCN 616 and the data plane VCN 618can be contained in a service tenancy 619 that can be owned and/oroperated by the IaaS provider.

The control plane VCN 616 can include a control plane demilitarized zone(DMZ) tier 620 that acts as a perimeter network (e.g., portions of acorporate network between the corporate intranet and external networks).The DMZ-based servers may have restricted responsibilities and help keepsecurity breaches contained. Additionally, the DMZ tier 620 can includeone or more load balancer (LB) subnet(s) 622, a control plane app tier624 that can include app subnet(s) 626, a control plane data tier 628that can include database (DB) subnet(s) 630 (e.g., frontend DBsubnet(s) and/or backend DB subnet(s)). The LB subnet(s) 622 containedin the control plane DMZ tier 620 can be communicatively coupled to theapp subnet(s) 626 contained in the control plane app tier 624 and anInternet gateway 634 that can be contained in the control plane VCN 616,and the app subnet(s) 626 can be communicatively coupled to the DBsubnet(s) 630 contained in the control plane data tier 628 and a servicegateway 636 and a network address translation (NAT) gateway 638. Thecontrol plane VCN 616 can include the service gateway 636 and the NATgateway 638.

The control plane VCN 616 can include a data plane mirror app tier 640that can include app subnet(s) 626. The app subnet(s) 626 contained inthe data plane mirror app tier 640 can include a virtual networkinterface controller (VNIC) 642 that can execute a compute instance 644.The compute instance 644 can communicatively couple the app subnet(s)626 of the data plane mirror app tier 640 to app subnet(s) 626 that canbe contained in a data plane app tier 646.

The data plane VCN 618 can include the data plane app tier 646, a dataplane DMZ tier 648, and a data plane data tier 650. The data plane DMZtier 648 can include LB subnet(s) 622 that can be communicativelycoupled to the app subnet(s) 626 of the data plane app tier 646 and theInternet gateway 634 of the data plane VCN 618. The app subnet(s) 626can be communicatively coupled to the service gateway 636 of the dataplane VCN 618 and the NAT gateway 638 of the data plane VCN 618. Thedata plane data tier 650 can also include the DB subnet(s) 630 that canbe communicatively coupled to the app subnet(s) 626 of the data planeapp tier 646.

The Internet gateway 634 of the control plane VCN 616 and of the dataplane VCN 618 can be communicatively coupled to a metadata managementservice 652 that can be communicatively coupled to public Internet 654.Public Internet 654 can be communicatively coupled to the NAT gateway638 of the control plane VCN 616 and of the data plane VCN 618. Theservice gateway 636 of the control plane VCN 616 and of the data planeVCN 618 can be communicatively couple to cloud services 656.

In some examples, the service gateway 636 of the control plane VCN 616or of the data plane VCN 618 can make application programming interface(API) calls to cloud services 656 without going through public Internet654. The API calls to cloud services 656 from the service gateway 636can be one-way: the service gateway 636 can make API calls to cloudservices 656, and cloud services 656 can send requested data to theservice gateway 636. But, cloud services 656 may not initiate API callsto the service gateway 636.

In some examples, the secure host tenancy 604 can be directly connectedto the service tenancy 619, which may be otherwise isolated. The securehost subnet 608 can communicate with the SSH subnet 614 through an LPG610 that may enable two-way communication over an otherwise isolatedsystem. Connecting the secure host subnet 608 to the SSH subnet 614 maygive the secure host subnet 608 access to other entities within theservice tenancy 619.

The control plane VCN 616 may allow users of the service tenancy 619 toset up or otherwise provision desired resources. Desired resourcesprovisioned in the control plane VCN 616 may be deployed or otherwiseused in the data plane VCN 618. In some examples, the control plane VCN616 can be isolated from the data plane VCN 618, and the data planemirror app tier 640 of the control plane VCN 616 can communicate withthe data plane app tier 646 of the data plane VCN 618 via VNICs 642 thatcan be contained in the data plane mirror app tier 640 and the dataplane app tier 646.

In some examples, users of the system, or customers, can make requests,for example create, read, update, or delete (CRUD) operations, throughpublic Internet 654 that can communicate the requests to the metadatamanagement service 652. The metadata management service 652 cancommunicate the request to the control plane VCN 616 through theInternet gateway 634. The request can be received by the LB subnet(s)622 contained in the control plane DMZ tier 620. The LB subnet(s) 622may determine that the request is valid, and in response to thisdetermination, the LB subnet(s) 622 can transmit the request to appsubnet(s) 626 contained in the control plane app tier 624. If therequest is validated and requires a call to public Internet 654, thecall to public Internet 654 may be transmitted to the NAT gateway 638that can make the call to public Internet 654. Memory that may bedesired to be stored by the request can be stored in the DB subnet(s)630.

In some examples, the data plane mirror app tier 640 can facilitatedirect communication between the control plane VCN 616 and the dataplane VCN 618. For example, changes, updates, or other suitablemodifications to configuration may be desired to be applied to theresources contained in the data plane VCN 618. Via a VNIC 642, thecontrol plane VCN 616 can directly communicate with, and can therebyexecute the changes, updates, or other suitable modifications toconfiguration to, resources contained in the data plane VCN 618.

In some embodiments, the control plane VCN 616 and the data plane VCN618 can be contained in the service tenancy 619. In this case, the user,or the customer, of the system may not own or operate either the controlplane VCN 616 or the data plane VCN 618. Instead, the IaaS provider mayown or operate the control plane VCN 616 and the data plane VCN 618,both of which may be contained in the service tenancy 619. Thisembodiment can enable isolation of networks that may prevent users orcustomers from interacting with other users', or other customers',resources. Also, this embodiment may allow users or customers of thesystem to store databases privately without needing to rely on publicInternet 654, which may not have a desired level of security, forstorage.

In other embodiments, the LB subnet(s) 622 contained in the controlplane VCN 616 can be configured to receive a signal from the servicegateway 636. In this embodiment, the control plane VCN 616 and the dataplane VCN 618 may be configured to be called by a customer of the IaaSprovider without calling public Internet 654. Customers of the IaaSprovider may desire this embodiment since database(s) that the customersuse may be controlled by the IaaS provider and may be stored on theservice tenancy 619, which may be isolated from public Internet 654.

FIG. 7 is a block diagram 700 illustrating another example pattern of anIaaS architecture, according to at least one embodiment. Serviceoperators 702 (e.g. service operators 602 of FIG. 6 ) can becommunicatively coupled to a secure host tenancy 704 (e.g. the securehost tenancy 604 of FIG. 6 ) that can include a virtual cloud network(VCN) 706 (e.g. the VCN 606 of FIG. 6 ) and a secure host subnet 708(e.g. the secure host subnet 608 of FIG. 6 ). The VCN 706 can include alocal peering gateway (LPG) 710 (e.g. the LPG 610 of FIG. 6 ) that canbe communicatively coupled to a secure shell (SSH) VCN 712 (e.g. the SSHVCN 612 of FIG. 6 ) via an LPG 610 contained in the SSH VCN 712. The SSHVCN 712 can include an SSH subnet 714 (e.g. the SSH subnet 614 of FIG. 6), and the SSH VCN 712 can be communicatively coupled to a control planeVCN 716 (e.g. the control plane VCN 616 of FIG. 6 ) via an LPG 710contained in the control plane VCN 716. The control plane VCN 716 can becontained in a service tenancy 719 (e.g. the service tenancy 619 of FIG.6 ), and the data plane VCN 718 (e.g. the data plane VCN 618 of FIG. 6 )can be contained in a customer tenancy 721 that may be owned or operatedby users, or customers, of the system.

The control plane VCN 716 can include a control plane DMZ tier 720 (e.g.the control plane DMZ tier 620 of FIG. 6 ) that can include LB subnet(s)722 (e.g. LB subnet(s) 622 of FIG. 6 ), a control plane app tier 724(e.g. the control plane app tier 624 of FIG. 6 ) that can include appsubnet(s) 726 (e.g. app subnet(s) 626 of FIG. 6 ), a control plane datatier 728 (e.g. the control plane data tier 628 of FIG. 6 ) that caninclude database (DB) subnet(s) 730 (e.g. similar to DB subnet(s) 630 ofFIG. 6 ). The LB subnet(s) 722 contained in the control plane DMZ tier720 can be communicatively coupled to the app subnet(s) 726 contained inthe control plane app tier 724 and an Internet gateway 734 (e.g. theInternet gateway 634 of FIG. 6 ) that can be contained in the controlplane VCN 716, and the app subnet(s) 726 can be communicatively coupledto the DB subnet(s) 730 contained in the control plane data tier 728 anda service gateway 736 (e.g. the service gateway of FIG. 6 ) and anetwork address translation (NAT) gateway 738 (e.g. the NAT gateway 638of FIG. 6 ). The control plane VCN 716 can include the service gateway736 and the NAT gateway 738.

The control plane VCN 716 can include a data plane mirror app tier 740(e.g. the data plane mirror app tier 640 of FIG. 6 ) that can includeapp subnet(s) 726. The app subnet(s) 726 contained in the data planemirror app tier 740 can include a virtual network interface controller(VNIC) 742 (e.g. the VNIC of 642) that can execute a compute instance744 (e.g. similar to the compute instance 644 of FIG. 6 ). The computeinstance 744 can facilitate communication between the app subnet(s) 726of the data plane mirror app tier 740 and the app subnet(s) 726 that canbe contained in a data plane app tier 746 (e.g. the data plane app tier646 of FIG. 6 ) via the VNIC 742 contained in the data plane mirror apptier 740 and the VNIC 742 contained in the data plane app tier 746.

The Internet gateway 734 contained in the control plane VCN 716 can becommunicatively coupled to a metadata management service 752 (e.g. themetadata management service 652 of FIG. 6 ) that can be communicativelycoupled to public Internet 754 (e.g. public Internet 654 of FIG. 6 ).Public Internet 754 can be communicatively coupled to the NAT gateway738 contained in the control plane VCN 716. The service gateway 736contained in the control plane VCN 716 can be communicatively couple tocloud services 756 (e.g. cloud services 656 of FIG. 6 ).

In some examples, the data plane VCN 718 can be contained in thecustomer tenancy 721. In this case, the IaaS provider may provide thecontrol plane VCN 716 for each customer, and the IaaS provider may, foreach customer, set up a unique compute instance 744 that is contained inthe service tenancy 719. Each compute instance 744 may allowcommunication between the control plane VCN 716, contained in theservice tenancy 719, and the data plane VCN 718 that is contained in thecustomer tenancy 721. The compute instance 744 may allow resources, thatare provisioned in the control plane VCN 716 that is contained in theservice tenancy 719, to be deployed or otherwise used in the data planeVCN 718 that is contained in the customer tenancy 721.

In other examples, the customer of the IaaS provider may have databasesthat live in the customer tenancy 721. In this example, the controlplane VCN 716 can include the data plane mirror app tier 740 that caninclude app subnet(s) 726. The data plane mirror app tier 740 can residein the data plane VCN 718, but the data plane mirror app tier 740 maynot live in the data plane VCN 718. That is, the data plane mirror apptier 740 may have access to the customer tenancy 721, but the data planemirror app tier 740 may not exist in the data plane VCN 718 or be ownedor operated by the customer of the IaaS provider. The data plane mirrorapp tier 740 may be configured to make calls to the data plane VCN 718but may not be configured to make calls to any entity contained in thecontrol plane VCN 716. The customer may desire to deploy or otherwiseuse resources in the data plane VCN 718 that are provisioned in thecontrol plane VCN 716, and the data plane mirror app tier 740 canfacilitate the desired deployment, or other usage of resources, of thecustomer.

In some embodiments, the customer of the IaaS provider can apply filtersto the data plane VCN 718. In this embodiment, the customer candetermine what the data plane VCN 718 can access, and the customer mayrestrict access to public Internet 754 from the data plane VCN 718. TheIaaS provider may not be able to apply filters or otherwise controlaccess of the data plane VCN 718 to any outside networks or databases.Applying filters and controls by the customer onto the data plane VCN718, contained in the customer tenancy 721, can help isolate the dataplane VCN 718 from other customers and from public Internet 754.

In some embodiments, cloud services 756 can be called by the servicegateway 736 to access services that may not exist on public Internet754, on the control plane VCN 716, or on the data plane VCN 718. Theconnection between cloud services 756 and the control plane VCN 716 orthe data plane VCN 718 may not be live or continuous. Cloud services 756may exist on a different network owned or operated by the IaaS provider.Cloud services 756 may be configured to receive calls from the servicegateway 736 and may be configured to not receive calls from publicInternet 754. Some cloud services 756 may be isolated from other cloudservices 756, and the control plane VCN 716 may be isolated from cloudservices 756 that may not be in the same region as the control plane VCN716. For example, the control plane VCN 716 may be located in “Region1,” and cloud service “Deployment 6,” may be located in Region 1 and in“Region 2.” If a call to Deployment 6 is made by the service gateway 736contained in the control plane VCN 716 located in Region 1, the call maybe transmitted to Deployment 6 in Region 1. In this example, the controlplane VCN 716, or Deployment 6 in Region 1, may not be communicativelycoupled to, or otherwise in communication with, Deployment 6 in Region2.

FIG. 8 is a block diagram 800 illustrating another example pattern of anIaaS architecture, according to at least one embodiment. Serviceoperators 802 (e.g. service operators 602 of FIG. 6 ) can becommunicatively coupled to a secure host tenancy 804 (e.g. the securehost tenancy 604 of FIG. 6 ) that can include a virtual cloud network(VCN) 806 (e.g. the VCN 606 of FIG. 6 ) and a secure host subnet 808(e.g. the secure host subnet 608 of FIG. 6 ). The VCN 806 can include anLPG 810 (e.g. the LPG 610 of FIG. 6 ) that can be communicativelycoupled to an SSH VCN 812 (e.g. the SSH VCN 612 of FIG. 6 ) via an LPG810 contained in the SSH VCN 812. The SSH VCN 812 can include an SSHsubnet 814 (e.g. the SSH subnet 614 of FIG. 6 ), and the SSH VCN 812 canbe communicatively coupled to a control plane VCN 816 (e.g. the controlplane VCN 616 of FIG. 6 ) via an LPG 810 contained in the control planeVCN 816 and to a data plane VCN 818 (e.g. the data plane 618 of FIG. 6 )via an LPG 810 contained in the data plane VCN 818. The control planeVCN 816 and the data plane VCN 818 can be contained in a service tenancy819 (e.g. the service tenancy 619 of FIG. 6 ).

The control plane VCN 816 can include a control plane DMZ tier 820 (e.g.the control plane DMZ tier 620 of FIG. 6 ) that can include loadbalancer (LB) subnet(s) 822 (e.g. LB subnet(s) 622 of FIG. 6 ), acontrol plane app tier 824 (e.g. the control plane app tier 624 of FIG.6 ) that can include app subnet(s) 826 (e.g. similar to app subnet(s)626 of FIG. 6 ), a control plane data tier 828 (e.g. the control planedata tier 628 of FIG. 6 ) that can include DB subnet(s) 830. The LBsubnet(s) 822 contained in the control plane DMZ tier 820 can becommunicatively coupled to the app subnet(s) 826 contained in thecontrol plane app tier 824 and to an Internet gateway 834 (e.g. theInternet gateway 634 of FIG. 6 ) that can be contained in the controlplane VCN 816, and the app subnet(s) 826 can be communicatively coupledto the DB subnet(s) 830 contained in the control plane data tier 828 andto a service gateway 836 (e.g. the service gateway of FIG. 6 ) and anetwork address translation (NAT) gateway 838 (e.g. the NAT gateway 638of FIG. 6 ). The control plane VCN 816 can include the service gateway836 and the NAT gateway 838.

The data plane VCN 818 can include a data plane app tier 846 (e.g. thedata plane app tier 646 of FIG. 6 ), a data plane DMZ tier 848 (e.g. thedata plane DMZ tier 648 of FIG. 6 ), and a data plane data tier 850(e.g. the data plane data tier 650 of FIG. 6 ). The data plane DMZ tier848 can include LB subnet(s) 822 that can be communicatively coupled totrusted app subnet(s) 860 and untrusted app subnet(s) 862 of the dataplane app tier 846 and the Internet gateway 834 contained in the dataplane VCN 818. The trusted app subnet(s) 860 can be communicativelycoupled to the service gateway 836 contained in the data plane VCN 818,the NAT gateway 838 contained in the data plane VCN 818, and DBsubnet(s) 830 contained in the data plane data tier 850. The untrustedapp subnet(s) 862 can be communicatively coupled to the service gateway836 contained in the data plane VCN 818 and DB subnet(s) 830 containedin the data plane data tier 850. The data plane data tier 850 caninclude DB subnet(s) 830 that can be communicatively coupled to theservice gateway 836 contained in the data plane VCN 818.

The untrusted app subnet(s) 862 can include one or more primary VNICs864(1)-(N) that can be communicatively coupled to tenant virtualmachines (VMs) 866(1)-(N). Each tenant VM 866(1)-(N) can becommunicatively coupled to a respective app subnet 867(1)-(N) that canbe contained in respective container egress VCNs 868(1)-(N) that can becontained in respective customer tenancies 870(1)-(N). Respectivesecondary VNICs 872(1)-(N) can facilitate communication between theuntrusted app subnet(s) 862 contained in the data plane VCN 818 and theapp subnet contained in the container egress VCNs 868(1)-(N). Eachcontainer egress VCNs 868(1)-(N) can include a NAT gateway 838 that canbe communicatively coupled to public Internet 854 (e.g. public Internet654 of FIG. 6 ).

The Internet gateway 834 contained in the control plane VCN 816 andcontained in the data plane VCN 818 can be communicatively coupled to ametadata management service 852 (e.g. the metadata management system 652of FIG. 6 ) that can be communicatively coupled to public Internet 854.Public Internet 854 can be communicatively coupled to the NAT gateway838 contained in the control plane VCN 816 and contained in the dataplane VCN 818. The service gateway 836 contained in the control planeVCN 816 and contained in the data plane VCN 818 can be communicativelycouple to cloud services 856.

In some embodiments, the data plane VCN 818 can be integrated withcustomer tenancies 870. This integration can be useful or desirable forcustomers of the IaaS provider in some cases such as a case that maydesire support when executing code. The customer may provide code to runthat may be destructive, may communicate with other customer resources,or may otherwise cause undesirable effects. In response to this, theIaaS provider may determine whether to run code given to the IaaSprovider by the customer.

In some examples, the customer of the IaaS provider may grant temporarynetwork access to the IaaS provider and request a function to beattached to the data plane tier app 846. Code to run the function may beexecuted in the VMs 866(1)-(N), and the code may not be configured torun anywhere else on the data plane VCN 818. Each VM 866(1)-(N) may beconnected to one customer tenancy 870. Respective containers 871(1)-(N)contained in the VMs 866(1)-(N) may be configured to run the code. Inthis case, there can be a dual isolation (e.g., the containers871(1)-(N) running code, where the containers 871(1)-(N) may becontained in at least the VM 866(1)-(N) that are contained in theuntrusted app subnet(s) 862), which may help prevent incorrect orotherwise undesirable code from damaging the network of the IaaSprovider or from damaging a network of a different customer. Thecontainers 871(1)-(N) may be communicatively coupled to the customertenancy 870 and may be configured to transmit or receive data from thecustomer tenancy 870. The containers 871(1)-(N) may not be configured totransmit or receive data from any other entity in the data plane VCN818. Upon completion of running the code, the IaaS provider may kill orotherwise dispose of the containers 871(1)-(N).

In some embodiments, the trusted app subnet(s) 860 may run code that maybe owned or operated by the IaaS provider. In this embodiment, thetrusted app subnet(s) 860 may be communicatively coupled to the DBsubnet(s) 830 and be configured to execute CRUD operations in the DBsubnet(s) 830. The untrusted app subnet(s) 862 may be communicativelycoupled to the DB subnet(s) 830, but in this embodiment, the untrustedapp subnet(s) may be configured to execute read operations in the DBsubnet(s) 830. The containers 871(1)-(N) that can be contained in the VM866(1)-(N) of each customer and that may run code from the customer maynot be communicatively coupled with the DB subnet(s) 830.

In other embodiments, the control plane VCN 816 and the data plane VCN818 may not be directly communicatively coupled. In this embodiment,there may be no direct communication between the control plane VCN 816and the data plane VCN 818. However, communication can occur indirectlythrough at least one method. An LPG 810 may be established by the IaaSprovider that can facilitate communication between the control plane VCN816 and the data plane VCN 818. In another example, the control planeVCN 816 or the data plane VCN 818 can make a call to cloud services 856via the service gateway 836. For example, a call to cloud services 856from the control plane VCN 816 can include a request for a service thatcan communicate with the data plane VCN 818.

FIG. 9 is a block diagram 900 illustrating another example pattern of anIaaS architecture, according to at least one embodiment. Serviceoperators 902 (e.g. service operators 602 of FIG. 6 ) can becommunicatively coupled to a secure host tenancy 904 (e.g. the securehost tenancy 604 of FIG. 6 ) that can include a virtual cloud network(VCN) 906 (e.g. the VCN 606 of FIG. 6 ) and a secure host subnet 908(e.g. the secure host subnet 608 of FIG. 6 ). The VCN 906 can include anLPG 910 (e.g. the LPG 610 of FIG. 6 ) that can be communicativelycoupled to an SSH VCN 912 (e.g. the SSH VCN 612 of FIG. 6 ) via an LPG910 contained in the SSH VCN 912. The SSH VCN 912 can include an SSHsubnet 914 (e.g. the SSH subnet 614 of FIG. 6 ), and the SSH VCN 912 canbe communicatively coupled to a control plane VCN 916 (e.g. the controlplane VCN 616 of FIG. 6 ) via an LPG 910 contained in the control planeVCN 916 and to a data plane VCN 918 (e.g. the data plane 618 of FIG. 6 )via an LPG 910 contained in the data plane VCN 918. The control planeVCN 916 and the data plane VCN 918 can be contained in a service tenancy919 (e.g. the service tenancy 619 of FIG. 6 ).

The control plane VCN 916 can include a control plane DMZ tier 920 (e.g.the control plane DMZ tier 620 of FIG. 6 ) that can include LB subnet(s)922 (e.g. LB subnet(s) 622 of FIG. 6 ), a control plane app tier 924(e.g. the control plane app tier 624 of FIG. 6 ) that can include appsubnet(s) 926 (e.g. app subnet(s) 626 of FIG. 6 ), a control plane datatier 928 (e.g. the control plane data tier 628 of FIG. 6 ) that caninclude DB subnet(s) 930 (e.g. DB subnet(s) 830 of FIG. 8 ). The LBsubnet(s) 922 contained in the control plane DMZ tier 920 can becommunicatively coupled to the app subnet(s) 926 contained in thecontrol plane app tier 924 and to an Internet gateway 934 (e.g. theInternet gateway 634 of FIG. 6 ) that can be contained in the controlplane VCN 916, and the app subnet(s) 926 can be communicatively coupledto the DB subnet(s) 930 contained in the control plane data tier 928 andto a service gateway 936 (e.g. the service gateway of FIG. 6 ) and anetwork address translation (NAT) gateway 938 (e.g. the NAT gateway 638of FIG. 6 ). The control plane VCN 916 can include the service gateway936 and the NAT gateway 938.

The data plane VCN 918 can include a data plane app tier 946 (e.g. thedata plane app tier 646 of FIG. 6 ), a data plane DMZ tier 948 (e.g. thedata plane DMZ tier 648 of FIG. 6 ), and a data plane data tier 950(e.g. the data plane data tier 650 of FIG. 6 ). The data plane DMZ tier948 can include LB subnet(s) 922 that can be communicatively coupled totrusted app subnet(s) 960 (e.g. trusted app subnet(s) 860 of FIG. 8 )and untrusted app subnet(s) 962 (e.g. untrusted app subnet(s) 862 ofFIG. 8 ) of the data plane app tier 946 and the Internet gateway 934contained in the data plane VCN 918. The trusted app subnet(s) 960 canbe communicatively coupled to the service gateway 936 contained in thedata plane VCN 918, the NAT gateway 938 contained in the data plane VCN918, and DB subnet(s) 930 contained in the data plane data tier 950. Theuntrusted app subnet(s) 962 can be communicatively coupled to theservice gateway 936 contained in the data plane VCN 918 and DB subnet(s)930 contained in the data plane data tier 950. The data plane data tier950 can include DB subnet(s) 930 that can be communicatively coupled tothe service gateway 936 contained in the data plane VCN 918.

The untrusted app subnet(s) 962 can include primary VNICs 964(1)-(N)that can be communicatively coupled to tenant virtual machines (VMs)966(1)-(N) residing within the untrusted app subnet(s) 962. Each tenantVM 966(1)-(N) can run code in a respective container 967(1)-(N), and becommunicatively coupled to an app subnet 926 that can be contained in adata plane app tier 946 that can be contained in a container egress VCN968. Respective secondary VNICs 972(1)-(N) can facilitate communicationbetween the untrusted app subnet(s) 962 contained in the data plane VCN918 and the app subnet contained in the container egress VCN 968. Thecontainer egress VCN can include a NAT gateway 938 that can becommunicatively coupled to public Internet 954 (e.g. public Internet 654of FIG. 6 ).

The Internet gateway 934 contained in the control plane VCN 916 andcontained in the data plane VCN 918 can be communicatively coupled to ametadata management service 952 (e.g. the metadata management system 652of FIG. 6 ) that can be communicatively coupled to public Internet 954.Public Internet 954 can be communicatively coupled to the NAT gateway938 contained in the control plane VCN 916 and contained in the dataplane VCN 918. The service gateway 936 contained in the control planeVCN 916 and contained in the data plane VCN 918 can be communicativelycouple to cloud services 956.

In some examples, the pattern illustrated by the architecture of blockdiagram 900 of FIG. 9 may be considered an exception to the patternillustrated by the architecture of block diagram 800 of FIG. 8 and maybe desirable for a customer of the IaaS provider if the IaaS providercannot directly communicate with the customer (e.g., a disconnectedregion). The respective containers 967(1)-(N) that are contained in theVMs 966(1)-(N) for each customer can be accessed in real-time by thecustomer. The containers 967(1)-(N) may be configured to make calls torespective secondary VNICs 972(1)-(N) contained in app subnet(s) 926 ofthe data plane app tier 946 that can be contained in the containeregress VCN 968. The secondary VNICs 972(1)-(N) can transmit the calls tothe NAT gateway 938 that may transmit the calls to public Internet 954.In this example, the containers 967(1)-(N) that can be accessed inreal-time by the customer can be isolated from the control plane VCN 916and can be isolated from other entities contained in the data plane VCN918. The containers 967(1)-(N) may also be isolated from resources fromother customers.

In other examples, the customer can use the containers 967(1)-(N) tocall cloud services 956. In this example, the customer may run code inthe containers 967(1)-(N) that requests a service from cloud services956. The containers 967(1)-(N) can transmit this request to thesecondary VNICs 972(1)-(N) that can transmit the request to the NATgateway that can transmit the request to public Internet 954. PublicInternet 954 can transmit the request to LB subnet(s) 922 contained inthe control plane VCN 916 via the Internet gateway 934. In response todetermining the request is valid, the LB subnet(s) can transmit therequest to app subnet(s) 926 that can transmit the request to cloudservices 956 via the service gateway 936.

It should be appreciated that IaaS architectures 600, 700, 800, 900depicted in the figures may have other components than those depicted.Further, the embodiments shown in the figures are only some examples ofa cloud infrastructure system that may incorporate an embodiment of thedisclosure. In some other embodiments, the IaaS systems may have more orfewer components than shown in the figures, may combine two or morecomponents, or may have a different configuration or arrangement ofcomponents.

In certain embodiments, the IaaS systems described herein may include asuite of applications, middleware, and database service offerings thatare delivered to a customer in a self-service, subscription-based,elastically scalable, reliable, highly available, and secure manner. Anexample of such an IaaS system is the Oracle Cloud Infrastructure (OCI)provided by the present assignee.

FIG. 10 illustrates an example computer system 1000, in which variousembodiments may be implemented. The system 1000 may be used to implementany of the computer systems described above. As shown in the figure,computer system 1000 includes a processing unit 1004 that communicateswith a number of peripheral subsystems via a bus subsystem 1002. Theseperipheral subsystems may include a processing acceleration unit 1006,an I/O subsystem 1008, a storage subsystem 1018 and a communicationssubsystem 1024. Storage subsystem 1018 includes tangiblecomputer-readable storage media 1022 and a system memory 1010.

Bus subsystem 1002 provides a mechanism for letting the variouscomponents and subsystems of computer system 1000 communicate with eachother as intended. Although bus subsystem 1002 is shown schematically asa single bus, alternative embodiments of the bus subsystem may utilizemultiple buses. Bus subsystem 1002 may be any of several types of busstructures including a memory bus or memory controller, a peripheralbus, and a local bus using any of a variety of bus architectures. Forexample, such architectures may include an Industry StandardArchitecture (ISA) bus, Micro Channel Architecture (MCA) bus, EnhancedISA (EISA) bus, Video Electronics Standards Association (VESA) localbus, and Peripheral Component Interconnect (PCI) bus, which can beimplemented as a Mezzanine bus manufactured to the IEEE P1386.1standard.

Processing unit 1004, which can be implemented as one or more integratedcircuits (e.g., a conventional microprocessor or microcontroller),controls the operation of computer system 1000. One or more processorsmay be included in processing unit 1004. These processors may includesingle core or multicore processors. In certain embodiments, processingunit 1004 may be implemented as one or more independent processing units1032 and/or 1034 with single or multicore processors included in eachprocessing unit. In other embodiments, processing unit 1004 may also beimplemented as a quad-core processing unit formed by integrating twodual-core processors into a single chip.

In various embodiments, processing unit 1004 can execute a variety ofprograms in response to program code and can maintain multipleconcurrently executing programs or processes. At any given time, some orall of the program code to be executed can be resident in processor(s)1004 and/or in storage subsystem 1018. Through suitable programming,processor(s) 1004 can provide various functionalities described above.Computer system 1000 may additionally include a processing accelerationunit 1006, which can include a digital signal processor (DSP), aspecial-purpose processor, and/or the like.

I/O subsystem 1008 may include user interface input devices and userinterface output devices. User interface input devices may include akeyboard, pointing devices such as a mouse or trackball, a touchpad ortouch screen incorporated into a display, a scroll wheel, a click wheel,a dial, a button, a switch, a keypad, audio input devices with voicecommand recognition systems, microphones, and other types of inputdevices. User interface input devices may include, for example, motionsensing and/or gesture recognition devices such as the Microsoft Kinect®motion sensor that enables users to control and interact with an inputdevice, such as the Microsoft Xbox® 360 game controller, through anatural user interface using gestures and spoken commands. Userinterface input devices may also include eye gesture recognition devicessuch as the Google Glass® blink detector that detects eye activity(e.g., ‘blinking’ while taking pictures and/or making a menu selection)from users and transforms the eye gestures as input into an input device(e.g., Google Glass®). Additionally, user interface input devices mayinclude voice recognition sensing devices that enable users to interactwith voice recognition systems (e.g., Siri® navigator), through voicecommands.

User interface input devices may also include, without limitation, threedimensional (3D) mice, joysticks or pointing sticks, gamepads andgraphic tablets, and audio/visual devices such as speakers, digitalcameras, digital camcorders, portable media players, webcams, imagescanners, fingerprint scanners, barcode reader 3D scanners, 3D printers,laser rangefinders, and eye gaze tracking devices. Additionally, userinterface input devices may include, for example, medical imaging inputdevices such as computed tomography, magnetic resonance imaging,position emission tomography, medical ultrasonography devices. Userinterface input devices may also include, for example, audio inputdevices such as MIDI keyboards, digital musical instruments and thelike.

User interface output devices may include a display subsystem, indicatorlights, or non-visual displays such as audio output devices, etc. Thedisplay subsystem may be a cathode ray tube (CRT), a flat-panel device,such as that using a liquid crystal display (LCD) or plasma display, aprojection device, a touch screen, and the like. In general, use of theterm “output device” is intended to include all possible types ofdevices and mechanisms for outputting information from computer system1000 to a user or other computer. For example, user interface outputdevices may include, without limitation, a variety of display devicesthat visually convey text, graphics and audio/video information such asmonitors, printers, speakers, headphones, automotive navigation systems,plotters, voice output devices, and modems.

Computer system 1000 may comprise a storage subsystem 1018 thatcomprises software elements, shown as being currently located within asystem memory 1010. System memory 1010 may store program instructionsthat are loadable and executable on processing unit 1004, as well asdata generated during the execution of these programs.

Depending on the configuration and type of computer system 1000, systemmemory 1010 may be volatile (such as random access memory (RAM)) and/ornon-volatile (such as read-only memory (ROM), flash memory, etc.) TheRAM typically contains data and/or program modules that are immediatelyaccessible to and/or presently being operated and executed by processingunit 1004. In some implementations, system memory 1010 may includemultiple different types of memory, such as static random access memory(SRAM) or dynamic random access memory (DRAM). In some implementations,a basic input/output system (BIOS), containing the basic routines thathelp to transfer information between elements within computer system1000, such as during start-up, may typically be stored in the ROM. Byway of example, and not limitation, system memory 1010 also illustratesapplication programs 1012, which may include client applications, Webbrowsers, mid-tier applications, relational database management systems(RDBMS), etc., program data 1014, and an operating system 1016. By wayof example, operating system 1016 may include various versions ofMicrosoft Windows®, Apple Macintosh®, and/or Linux operating systems, avariety of commercially-available UNIX® or UNIX-like operating systems(including without limitation the variety of GNU/Linux operatingsystems, the Google Chrome® OS, and the like) and/or mobile operatingsystems such as iOS, Windows® Phone, Android® OS, BlackBerry® 10 OS, andPalm® OS operating systems.

Storage subsystem 1018 may also provide a tangible computer-readablestorage medium for storing the basic programming and data constructsthat provide the functionality of some embodiments. Software (programs,code modules, instructions) that when executed by a processor providethe functionality described above may be stored in storage subsystem1018. These software modules or instructions may be executed byprocessing unit 1004. Storage subsystem 1018 may also provide arepository for storing data used in accordance with the presentdisclosure.

Storage subsystem 1000 may also include a computer-readable storagemedia reader 1020 that can further be connected to computer-readablestorage media 1022. Together and, optionally, in combination with systemmemory 1010, computer-readable storage media 1022 may comprehensivelyrepresent remote, local, fixed, and/or removable storage devices plusstorage media for temporarily and/or more permanently containing,storing, transmitting, and retrieving computer-readable information.

Computer-readable storage media 1022 containing code, or portions ofcode, can also include any appropriate media known or used in the art,including storage media and communication media, such as but not limitedto, volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage and/or transmissionof information. This can include tangible computer-readable storagemedia such as RAM, ROM, electronically erasable programmable ROM(EEPROM), flash memory or other memory technology, CD-ROM, digitalversatile disk (DVD), or other optical storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or other tangible computer readable media. This can also includenontangible computer-readable media, such as data signals, datatransmissions, or any other medium which can be used to transmit thedesired information and which can be accessed by computing system 1000.

By way of example, computer-readable storage media 1022 may include ahard disk drive that reads from or writes to non-removable, nonvolatilemagnetic media, a magnetic disk drive that reads from or writes to aremovable, nonvolatile magnetic disk, and an optical disk drive thatreads from or writes to a removable, nonvolatile optical disk such as aCD ROM, DVD, and Blu-Ray® disk, or other optical media.Computer-readable storage media 1022 may include, but is not limited to,Zip® drives, flash memory cards, universal serial bus (USB) flashdrives, secure digital (SD) cards, DVD disks, digital video tape, andthe like. Computer-readable storage media 1022 may also include,solid-state drives (SSD) based on non-volatile memory such asflash-memory based SSDs, enterprise flash drives, solid state ROM, andthe like, SSDs based on volatile memory such as solid state RAM, dynamicRAM, static RAM, DRAM-based SSDs, magnetoresistive RAM (MRAM) SSDs, andhybrid SSDs that use a combination of DRAM and flash memory based SSDs.The disk drives and their associated computer-readable media may providenon-volatile storage of computer-readable instructions, data structures,program modules, and other data for computer system 1000.

Communications subsystem 1024 provides an interface to other computersystems and networks. Communications subsystem 1024 serves as aninterface for receiving data from and transmitting data to other systemsfrom computer system 1000. For example, communications subsystem 1024may enable computer system 1000 to connect to one or more devices viathe Internet. In some embodiments communications subsystem 1024 caninclude radio frequency (RF) transceiver components for accessingwireless voice and/or data networks (e.g., using cellular telephonetechnology, advanced data network technology, such as 3G, 4G or EDGE(enhanced data rates for global evolution), WiFi (IEEE 802.11 familystandards, or other mobile communication technologies, or anycombination thereof), global positioning system (GPS) receivercomponents, and/or other components. In some embodiments communicationssubsystem 1024 can provide wired network connectivity (e.g., Ethernet)in addition to or instead of a wireless interface.

In some embodiments, communications subsystem 1024 may also receiveinput communication in the form of structured and/or unstructured datafeeds 1026, event streams 1028, event updates 1030, and the like onbehalf of one or more users who may use computer system 1000.

By way of example, communications subsystem 1024 may be configured toreceive data feeds 1026 in real-time from users of social networksand/or other communication services such as Twitter® feeds, Facebook®updates, web feeds such as Rich Site Summary (RSS) feeds, and/orreal-time updates from one or more third party information sources.

Additionally, communications subsystem 1024 may also be configured toreceive data in the form of continuous data streams, which may includeevent streams 1028 of real-time events and/or event updates 1030, thatmay be continuous or unbounded in nature with no explicit end. Examplesof applications that generate continuous data may include, for example,sensor data applications, financial tickers, network performancemeasuring tools (e.g. network monitoring and traffic managementapplications), clickstream analysis tools, automobile trafficmonitoring, and the like.

Communications subsystem 1024 may also be configured to output thestructured and/or unstructured data feeds 1026, event streams 1028,event updates 1030, and the like to one or more databases that may be incommunication with one or more streaming data source computers coupledto computer system 1000.

Computer system 1000 can be one of various types, including a handheldportable device (e.g., an iPhone® cellular phone, an iPad® computingtablet, a PDA), a wearable device (e.g., a Google Glass® head mounteddisplay), a PC, a workstation, a mainframe, a kiosk, a server rack, orany other data processing system.

Due to the ever-changing nature of computers and networks, thedescription of computer system 1000 depicted in the figure is intendedonly as a specific example. Many other configurations having more orfewer components than the system depicted in the figure are possible.For example, customized hardware might also be used and/or particularelements might be implemented in hardware, firmware, software (includingapplets), or a combination. Further, connection to other computingdevices, such as network input/output devices, may be employed. Based onthe disclosure and teachings provided herein, a person of ordinary skillin the art will appreciate other ways and/or methods to implement thevarious embodiments.

Although specific embodiments have been described, variousmodifications, alterations, alternative constructions, and equivalentsare also encompassed within the scope of the disclosure. Embodiments arenot restricted to operation within certain specific data processingenvironments, but are free to operate within a plurality of dataprocessing environments. Additionally, although embodiments have beendescribed using a particular series of transactions and steps, it shouldbe apparent to those skilled in the art that the scope of the presentdisclosure is not limited to the described series of transactions andsteps. Various features and aspects of the above-described embodimentsmay be used individually or jointly.

Further, while embodiments have been described using a particularcombination of hardware and software, it should be recognized that othercombinations of hardware and software are also within the scope of thepresent disclosure. Embodiments may be implemented only in hardware, oronly in software, or using combinations thereof. The various processesdescribed herein can be implemented on the same processor or differentprocessors in any combination. Accordingly, where components or modulesare described as being configured to perform certain operations, suchconfiguration can be accomplished, e.g., by designing electroniccircuits to perform the operation, by programming programmableelectronic circuits (such as microprocessors) to perform the operation,or any combination thereof. Processes can communicate using a variety oftechniques including but not limited to conventional techniques forinter process communication, and different pairs of processes may usedifferent techniques, or the same pair of processes may use differenttechniques at different times.

The specification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense. It will, however, beevident that additions, subtractions, deletions, and other modificationsand changes may be made thereunto without departing from the broaderspirit and scope as set forth in the claims. Thus, although specificdisclosure embodiments have been described, these are not intended to belimiting. Various modifications and equivalents are within the scope ofthe following claims.

The use of the terms “a” and “an” and “the” and similar referents in thecontext of describing the disclosed embodiments (especially in thecontext of the following claims) are to be construed to cover both thesingular and the plural, unless otherwise indicated herein or clearlycontradicted by context. The terms “comprising,” “having,” “including,”and “containing” are to be construed as open-ended terms (i.e., meaning“including, but not limited to,”) unless otherwise noted. The term“connected” is to be construed as partly or wholly contained within,attached to, or joined together, even if there is something intervening.Recitation of ranges of values herein are merely intended to serve as ashorthand method of referring individually to each separate valuefalling within the range, unless otherwise indicated herein and eachseparate value is incorporated into the specification as if it wereindividually recited herein. All methods described herein can beperformed in any suitable order unless otherwise indicated herein orotherwise clearly contradicted by context. The use of any and allexamples, or exemplary language (e.g., “such as”) provided herein, isintended merely to better illuminate embodiments and does not pose alimitation on the scope of the disclosure unless otherwise claimed. Nolanguage in the specification should be construed as indicating anynon-claimed element as essential to the practice of the disclosure.

Disjunctive language such as the phrase “at least one of X, Y, or Z,”unless specifically stated otherwise, is intended to be understoodwithin the context as used in general to present that an item, term,etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y,and/or Z). Thus, such disjunctive language is not generally intended to,and should not, imply that certain embodiments require at least one ofX, at least one of Y, or at least one of Z to each be present.

Preferred embodiments of this disclosure are described herein, includingthe best mode known for carrying out the disclosure. Variations of thosepreferred embodiments may become apparent to those of ordinary skill inthe art upon reading the foregoing description. Those of ordinary skillshould be able to employ such variations as appropriate and thedisclosure may be practiced otherwise than as specifically describedherein. Accordingly, this disclosure includes all modifications andequivalents of the subject matter recited in the claims appended heretoas permitted by applicable law. Moreover, any combination of theabove-described elements in all possible variations thereof isencompassed by the disclosure unless otherwise indicated herein.

All references, including publications, patent applications, andpatents, cited herein are hereby incorporated by reference to the sameextent as if each reference were individually and specifically indicatedto be incorporated by reference and were set forth in its entiretyherein.

In the foregoing specification, aspects of the disclosure are describedwith reference to specific embodiments thereof, but those skilled in theart will recognize that the disclosure is not limited thereto. Variousfeatures and aspects of the above-described disclosure may be usedindividually or jointly. Further, embodiments can be utilized in anynumber of environments and applications beyond those described hereinwithout departing from the broader spirit and scope of thespecification. The specification and drawings are, accordingly, to beregarded as illustrative rather than restrictive.

What is claimed is:
 1. A method, comprising: for a first entity deployedin a first region of a cloud services provider network, monitoring, by acomputer system, a flow of network traffic data originating from thefirst entity and destined to a second entity remote from the firstentity; based at least in part on the monitoring, determining, by thecomputer system, that the flow of network traffic data originating fromthe first entity exceeds a threshold value, wherein the first entity isa first customer network of the cloud services provider network, and thesecond entity is a second customer network of the cloud servicesprovider network; responsive to the determining, identifying, by thecomputer system, an action to be taken to mitigate the threshold valuebeing exceeded; and performing, by the computer system, the action tomitigate the threshold value being exceeded.
 2. The method of claim 1,wherein monitoring, by the computer system, the flow of network trafficdata originating from the first entity further comprises: analyzing, bythe computer system, a plurality of network traffic data values relatedto the flow of network traffic data from a cluster of internal routingdevices within the cloud services provider network; and based at leastin part on the analysis, determining, by the computer system, that theat least one network traffic data value related to the flow of thenetwork traffic data exceeds a first threshold value.
 3. The method ofclaim 2, wherein the least one network traffic data value comprises atleast one of a packet generation frequency or a packet size related topackets in the flow of network traffic data.
 4. The method of claim 2,further comprising transmitting, by the computer system, a first alertto a user of the cloud services provider network based at least in parton determining that the at least one network traffic data value relatedto the flow of network traffic data exceeds the first threshold value.5. The method of claim 2, wherein the first alert is transmitted as anemail message to a user of the cloud services provider network.
 6. Themethod of claim 4, wherein monitoring, by the computer system, the flowof network traffic data originating from the first entity furthercomprises: analyzing, by the computer system, the plurality of networktraffic data values related to the flow of network traffic data from thecluster of internal routing devices within the cloud services providernetwork; and based at least in part on the analysis, determining, by thecomputer system, that the at least one network traffic data valuerelated to the flow of network traffic data exceeds a second thresholdvalue, wherein the second threshold value is greater than the firstthreshold value.
 7. The method of claim 6, further comprising,triggering, by the computer system, an internal mitigation plan tomitigate a Denial of Service attack based at least in part ondetermining that the at least one network traffic data value related tothe flow of network traffic data exceeds the second threshold value. 8.The method of claim 7, wherein the internal mitigation plan identifies aset of one or more actions to mitigate the Denial of Service attack,wherein a first action in the set of one or more actions comprisestransmitting, by the computer system, an instruction to the cluster ofinternal routing devices to limit a rate of the flow of network trafficdata from the first entity to the second entity.
 9. The method of claim8, wherein a second action in the set of one or more actions comprisestransmitting, by the computer system, an instruction to the cluster ofinternal routing devices to tag a prefix of an Internet Protocol addressof the first entity to block the flow of network traffic datatransmitted from the first entity to the second entity.
 10. The methodof claim 8, wherein a third action in the set of one or more actionscomprises transmitting, by the computer system, an instruction to thecluster of internal routing devices to divert the flow of networktraffic data transmitted from the first entity to a Remote triggeredBlackhole (RTBH).
 11. The method of claim 1, wherein the second entityis deployed in a second region of the cloud services provider network,wherein the cloud services provider network is configured to provision aset of infrastructure resources for deployment by the second entity inthe second region.
 12. The method of claim 1, wherein the second entityis an external entity deployed in a network external to the cloudservices provider network.
 13. The method of claim 1, wherein thethreshold value identifies at least one network traffic data valuerelated to the flow of network traffic data indicative of a Denial ofService attack in the cloud services provider network, wherein theDenial of Service attack comprises at least one of a volumetric Denialof Service attack or a volumetric Distributed Denial of Service attackin the cloud services provider network.
 14. A system comprising: aprocessor; and a memory storing instructions that, when executed by theprocessor, configure the system to: for a first entity deployed in afirst region of a cloud services provider network, monitor a flow ofnetwork traffic data originating from the first entity and destined to asecond entity remote from the first entity; based at least in part onthe monitoring, determine that the flow of network traffic dataoriginating from the first entity exceeds a threshold value, wherein thefirst entity is a first customer network of the cloud services providernetwork, and the second entity is a second customer network of the cloudservices provider network; responsive to the determining, identify anaction to be taken to mitigate the threshold value being exceeded; andperform the action to mitigate the threshold value being exceeded. 15.The system of claim 14, wherein the instructions to monitor the flow ofnetwork traffic data originating from the first entity further comprisesinstructions to: analyze a plurality of network traffic data valuesrelated to the flow of network traffic data from a cluster of internalrouting devices within the cloud service provider network; and based atleast in part on the analysis, determine that the at least one networktraffic data value related to the flow of network traffic data exceeds afirst threshold value.
 16. The system of claim 15, further comprisinginstructions to transmit a first alert to a user of the cloud servicesprovider network based at least in part on determining that the at leastone network traffic data value related to the flow of network trafficdata exceeds the first threshold value.
 17. The system of claim 13,wherein the second entity is deployed in a second region of the cloudservices provider network, wherein the cloud services provider networkis configured to provision a set of infrastructure resources fordeployment by the second entity in the second region.
 18. Anon-transitory computer-readable medium having program code that isstored thereon, the program code executable by one or more processingdevices for performing operations comprising: for a first entitydeployed in a first region of a cloud services provider network,monitoring a flow of network traffic data originating from the firstentity and destined to a second entity remote from the first entity;based at least in part on the monitoring, determining that the flow ofnetwork traffic data originating from the first entity exceeds athreshold value, wherein the first entity is a first customer network ofthe cloud services provider network, and the second entity is a secondcustomer network of the cloud services provider network; responsive tothe determining, identifying an action to be taken to mitigate thethreshold value being exceeded; and performing the action to mitigatethe threshold value being exceeded.
 19. The computer-readable medium ofclaim 18, wherein the monitoring further comprises: analyzing aplurality of network traffic data values related to the flow of networktraffic data from a cluster of internal routing devices within the cloudservices provider network; and based at least in part on the analysis,determining that the at least one network traffic data value related tothe flow of network traffic data exceeds a first threshold value. 20.The computer-readable medium of claim 18, wherein the least one networktraffic data value comprises at least one of a packet generationfrequency or a packet size related to packets in the flow of networktraffic data.